BlackboxBook/.github/review-cache/authoritative-sources-by-topic.md

Authoritative Sources for LLM Fact-Checking — by Topic

Generated 2026-05-20. Covers all 24 content chapters. Sources are primary papers, official docs, benchmarks, and authoritative blogs (no Medium, Substack, Twitter, YouTube, news).

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1. Tokenizers, Embeddings, Semantic Space

Foundational

Source	Authors	Year	Venue	Why Authoritative
Neural Machine Translation of Rare Words with Subword Units	Sennrich, Haddow, Birch	2016	ACL	Introduced BPE for NLP; 4000+ citations
SentencePiece: A simple and language independent subword tokenizer and detokenizer	Kudo & Richardson	2018	EMNLP	Standard tokenizer library; 3000+ citations
Efficient Estimation of Word Representations in Vector Space	Mikolov et al.	2013	ICLR (workshop)	Word2Vec — foundational embedding work; 40000+ citations
GloVe: Global Vectors for Word Representation	Pennington, Socher, Manning	2014	EMNLP	Foundational dense embeddings; 40000+ citations
BERT: Pre-training of Deep Bidirectional Transformers	Devlin, Chang, Lee, Toutanova	2019	NAACL	Bidirectional pre-training paradigm; 70000+ citations
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks	Reimers & Gurevych	2019	EMNLP	Sentence-level embeddings standard

Benchmarks & Tools

Source	Authors/Org	Year	Venue	Why Authoritative
MTEB: Massive Text Embedding Benchmark	Muennighoff et al.	2023	EACL	Standard embedding benchmark; HuggingFace leaderboard
tiktoken	OpenAI	2022–	GitHub repo	Official BPE tokenizer for GPT models
HuggingFace Tokenizers	HuggingFace	2019–	Library	Industry-standard tokenizer library

Modern Contextual Embeddings

Source	Authors	Year	Venue	Why Authoritative
Matryoshka Representation Learning	Kusupati et al.	2022	NeurIPS	Matryoshka embeddings — variable-size representations
Text and Code Embeddings by Contrastive Pre-Training	Neelakantan et al. (OpenAI)	2022	arXiv:2201.10005	OpenAI embedding models (text-embedding-ada-002)

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2. Transformer Architecture, Attention, MLP Layers

Architecture Foundation

Source	Authors	Year	Venue	Why Authoritative
Attention Is All You Need	Vaswani et al.	2017	NeurIPS	Original Transformer; 130000+ citations
GLU Variants Improve Transformer	Shazeer	2020	arXiv:2002.05202	SwiGLU — activation used in modern LLMs
Transformer Feed-Forward Layers Are Key-Value Memories	Geva et al.	2021	EMNLP	MLP layers as associative memory; foundational interpretability
Gaussian Error Linear Units (GELUs)	Hendrycks & Gimpel	2016	arXiv:1606.08415	GELU activation; used in GPT/BERT
Layer Normalization	Ba, Kiros, Hinton	2016	arXiv:1607.06450	LayerNorm — foundational; 8000+ citations

Attention Variants

Source	Authors	Year	Venue	Why Authoritative
Fast Transformer Decoding: One Write-Head is All You Need	Shazeer	2019	arXiv:1911.02150	Multi-Query Attention (MQA)
GQA: Training Generalized Multi-Query Transformer Models	Ainslie et al.	2023	EMNLP	Grouped-Query Attention (GQA) — used in Llama, Gemma
FlashAttention: Fast and Memory-Efficient Exact Attention	Dao et al.	2022	NeurIPS	IO-aware exact attention; enables long context
FlashAttention-2: Faster Attention with Better Parallelism	Dao	2023	arXiv:2307.08691	Improved parallelism + work partitioning
FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision	Shah et al.	2024	arXiv:2407.08608	Hopper GPU optimizations
Ring Attention with Blockwise Transformers for Near-Infinite Context	Liu et al.	2023	arXiv:2310.01889	Distributed attention for ultra-long context

Positional Encodings

Source	Authors	Year	Venue	Why Authoritative
RoFormer: Enhanced Transformer with Rotary Position Embedding	Su et al.	2021	arXiv:2104.09864	RoPE — standard in Llama, Qwen, DeepSeek, Gemma
Train Short, Test Long: Attention with Linear Biases (ALiBi)	Press et al.	2022	ICLR	ALiBi — length extrapolation without positional embeddings
YaRN: Efficient Context Window Extension	Peng et al.	2023	arXiv:2309.00071	RoPE interpolation for context extension

MoE (Mixture of Experts)

Source	Authors	Year	Venue	Why Authoritative
Outrageously Large Neural Networks: The Sparsely-Gated MoE Layer	Shazeer et al.	2017	ICLR	Original MoE for language models
Switch Transformers: Scaling to Trillion Parameter Models	Fedus et al.	2021	JMLR	Simplified MoE routing; T5-based
Mixtral of Experts	Jiang et al. (Mistral AI)	2024	arXiv:2401.04088	Production MoE: 8×7B, outperforms Llama 2 70B
DeepSeek-V3 Technical Report	DeepSeek-AI	2024	arXiv:2412.19437	671B MoE with multi-token prediction

Interpretability

Source	Authors	Year	Venue	Why Authoritative
Knowledge Neurons in Pretrained Transformers	Dai et al.	2022	ACL	Factual knowledge localization
Locating and Editing Factual Associations in GPT	Meng et al.	2022	NeurIPS	ROME — causal tracing of facts
Mass-Editing Memory in a Transformer	Meng et al.	2023	ICLR	MEMIT — batched fact editing
Towards Monosemanticity: Decomposing LMs With Dictionary Learning	Bricken et al. (Anthropic)	2023	Transformer Circuits	Sparse autoencoders for features
Scaling Monosemanticity	Templeton et al. (Anthropic)	2024	Anthropic Research	Feature extraction from Claude 3 Sonnet
Transformers represent belief state geometry in their residual stream	Shai et al.	2024	arXiv:2405.15943	Belief state geometry
The Geometry of Reasoning	Zhou et al.	2025	arXiv:2510.09782	Reasoning geometry in representation space

State Space Models / Hybrids

Source	Authors	Year	Venue	Why Authoritative
Efficiently Modeling Long Sequences with Structured State Spaces (S4)	Gu et al.	2021	ICLR 2022	Original S4 — linear-time sequence modeling
Mamba: Linear-Time Sequence Modeling with Selective State Spaces	Gu & Dao	2023	arXiv:2312.00752	Selective SSM; linear attention alternative
Transformers are SSMs (Mamba-2)	Dao & Gu	2024	ICML	Unified framework; SSD layer
Jamba: A Hybrid Transformer-Mamba Language Model	Lieber et al. (AI21)	2024	arXiv:2403.19887	Production hybrid; Transformer + Mamba + MoE
Jamba 2	AI21 Labs	2026	ai21.com/blog	Apache 2.0 hybrid, 256K context

Scaling Laws

Source	Authors	Year	Venue	Why Authoritative
Scaling Laws for Neural Language Models	Kaplan et al. (OpenAI)	2020	arXiv:2001.08361	Power-law scaling; 2000+ citations
Training Compute-Optimal Large Language Models (Chinchilla)	Hoffmann et al. (DeepMind)	2022	NeurIPS	Optimal compute allocation; 2000+ citations

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3. Hallucinations in LLMs

Surveys & Taxonomies

Source	Authors	Year	Venue	Why Authoritative
Survey of Hallucination in Natural Language Generation	Ji et al.	2023	ACM Computing Surveys	Canonical hallucination taxonomy; 1500+ citations
A Survey on Hallucination in Large Language Models	Huang et al.	2023	arXiv:2311.05232	Comprehensive causes + mitigation review

Benchmarks & Metrics

Source	Authors	Year	Venue	Why Authoritative
TruthfulQA: Measuring How Models Mimic Human Falsehoods	Lin et al.	2022	ACL	Standard truthfulness benchmark
FActScore: Fine-grained Atomic Evaluation of Factual Precision	Min et al.	2023	EMNLP	Atomic fact verification metric
SimpleQA: Measuring Short-form Factuality	OpenAI	2024	openai.com/index/simpleqa	OpenAI factual accuracy benchmark
ClashEval: Quantifying the tug-of-war between an LLM's internal prior and external evidence	Wu, Wu, Zou	2025	arXiv:2404.10198	Measures prior vs. evidence conflict

Mechanisms & Detection

Source	Authors	Year	Venue	Why Authoritative
Language Models Don't Always Say What They Think	Turpin et al.	2023	NeurIPS	Unfaithful CoT explanations
Measuring Faithfulness in Chain-of-Thought Reasoning	Lanham et al.	2023	arXiv:2307.13702	CoT faithfulness metrics
Towards Understanding Sycophancy in Language Models	Sharma et al.	2024	ICLR	Sycophancy — models agreeing with user bias

Mitigation

Source	Authors	Year	Venue	Why Authoritative
Chain-of-Verification Reduces Hallucination	Dhuliawala et al.	2023	arXiv:2309.11495	CoVe — self-verification loop
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks	Lewis et al.	2020	NeurIPS	Original RAG as anti-hallucination

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4. Causal Decoding, Context Windows, Long Context

Position & Context Mechanics

Source	Authors	Year	Venue	Why Authoritative
Lost in the Middle: How Language Models Use Long Contexts	Liu et al.	2023	TACL	U-shaped attention curve in long context
Efficient Streaming Language Models with Attention Sinks	Xiao et al.	2023	ICLR 2024	StreamingLLM — initial tokens as attention sinks
Longformer: The Long-Document Transformer	Beltagy et al.	2020	arXiv:2004.05150	Sparse attention for long documents
Big Bird: Transformers for Longer Sequences	Zaheer et al.	2020	NeurIPS	Sparse + global + random attention

Context Extension

Source	Authors	Year	Venue	Why Authoritative
YaRN: Efficient Context Window Extension	Peng et al.	2023	arXiv:2309.00071	NTK-aware RoPE interpolation; widely adopted
Self-Extend: Extending LLM Context Windows	Jin et al.	2024	arXiv:2401.01325	Training-free extension via grouped attention
HELMET: How to Evaluate Long-context LMs Effectively and Thoroughly	Yen et al.	2024	arXiv:2410.02666	Long-context eval framework

Causal Masking Fundamentals

Source	Authors	Year	Venue	Why Authoritative
Language Models are Unsupervised Multitask Learners (GPT-2)	Radford et al. (OpenAI)	2019	OpenAI Blog	Causal (autoregressive) LM paradigm formalized
Language Models are Few-Shot Learners (GPT-3)	Brown et al.	2020	NeurIPS	Scaling causal LM to 175B; in-context learning

Diffusion LLM (alternatives to causal)

Source	Authors	Year	Venue	Why Authoritative
Simple and Effective Masked Diffusion Language Models	Sahoo et al.	2024	NeurIPS	MDLM — masked diffusion for text
Discrete Diffusion Modeling (SEDD)	Lou et al.	2024	ICML	Score entropy discrete diffusion
Large Language Diffusion Models (LLaDA)	Nie et al.	2025	arXiv:2502.09992	8B diffusion model matching LLaMA3
Mercury: The Fastest LLM	Inception Labs	2025–2026	inceptionlabs.ai	First production diffusion LLM

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5. Prompt Engineering, XML Markup, Chain-of-Thought

Prompting Methods

Source	Authors	Year	Venue	Why Authoritative
Chain-of-Thought Prompting Elicits Reasoning in LLMs	Wei et al. (Google)	2022	NeurIPS	Introduced CoT; 3000+ citations
Large Language Models are Zero-Shot Reasoners	Kojima et al.	2022	NeurIPS	"Let's think step by step"
Plan-and-Solve Prompting	Wang et al.	2023	ACL	Structured planning in zero-shot
Decomposed Prompting: A Modular Approach	Khot et al.	2023	ICLR	Task decomposition via prompting
Least-to-Most Prompting	Zhou et al.	2023	ICLR	Progressive complexity prompting

Structured Output & Prompt Architecture

Source	Org	Year	Type	Why Authoritative
Use XML tags to structure your prompts	Anthropic	2024–2026	Official docs	Primary guidance on XML markup for Claude
Prompt engineering best practices	OpenAI	2024–2026	Official docs	Prompt structure for OpenAI models
Structured Outputs API	OpenAI	2024–2026	Official docs	JSON Schema constrained decoding
Efficient Guided Generation for LLMs (Outlines)	Willard & Louf	2023	arXiv:2307.09702	Structured generation via FSM
Guidance	Microsoft	2023–	GitHub repo	DSL for controlling LLM output structure
LMQL	Beurer-Kellner et al.	2023–2025	arXiv	SQL-like language for LLM constraints

Prompt Optimization

Source	Authors	Year	Venue	Why Authoritative
DSPy: Compiling Declarative Language Model Calls	Khattab et al.	2024	ICLR/TMLR	Automated prompt optimization via signatures
Large Language Models as Optimizers (OPRO)	Yang et al.	2024	ICLR	LLMs as prompt optimizers
The Unreasonable Effectiveness of Eccentric Automatic Prompts	Battle & Gollapudi	2024	arXiv	Systematic prompt search

Agent-Specific Prompting

Source	Authors	Year	Venue	Why Authoritative
ReAct: Synergizing Reasoning and Acting	Yao et al.	2023	ICLR	Interleaved reasoning + action
Reflexion: Language Agents with Verbal RL	Shinn et al.	2023	NeurIPS	Self-reflection via verbal feedback
Tree of Thoughts	Yao et al.	2023	NeurIPS	Tree search over reasoning paths
Graph of Thoughts	Besta et al.	2024	AAAI	Graph-based reasoning framework
Language Agent Tree Search (LATS)	Zhou et al.	2024	arXiv:2310.04406	Unified reasoning + acting + planning

Prompt Safety & Alignment

Source	Authors	Year	Venue	Why Authoritative
Constitutional AI: Harmlessness from AI Feedback	Bai et al. (Anthropic)	2022	arXiv:2212.08073	Self-critique + revision via constitution
Calibrate Before Use	Zhao et al.	2021	ICML	Few-shot calibration; format sensitivity

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6. Agents vs Chat, Tool Use, MCP Protocol

Agent Foundations

Source	Authors	Year	Venue	Why Authoritative
ReAct: Synergizing Reasoning and Acting in Language Models	Yao et al.	2023	ICLR	Defines agent loop: Thought → Action → Observation
Cognitive Architectures for Language Agents (CoALA)	Sumers, Yao, Narasimhan, Griffiths	2023	TMLR 2024	Cognitive framework for LLM agents
Generative Agents: Interactive Simulacra of Human Behavior	Park et al.	2023	UIST	Agent memory + reflection architecture
Building Effective Agents	Anthropic	2024	anthropic.com/research	Definitive agent design patterns guide
A Practical Guide to Building Agents	OpenAI	2025	platform.openai.com	OpenAI agent building patterns

Tool Use

Source	Authors	Year	Venue	Why Authoritative
Toolformer: Language Models Can Teach Themselves to Use Tools	Schick et al. (Meta)	2023	NeurIPS	Self-supervised tool learning
PAL: Program-aided Language Models	Gao et al.	2023	ICML	Code as reasoning + computation
Tool Learning with Foundation Models	Qin et al.	2024	Nature Machine Intelligence	Comprehensive tool-learning survey
Tool Use API docs	Anthropic	2024–2026	Official docs	Native tool calling for Claude
Tools, Connectors, and MCP	OpenAI	2025–2026	Official docs	Tool use in Responses API
Computer Use	Anthropic	2024–2026	Official docs	GUI agent capabilities
Code Execution Tool	Anthropic	2026	Official docs	Sandboxed code execution for agents

MCP Ecosystem

Source	Org	Year	Type	Why Authoritative
MCP Specification (v2025-11-25)	Anthropic / LF Projects	2024–2025	Formal spec	Canonical MCP protocol definition
MCP Introduction & Concepts	Anthropic	2024–2026	Official docs	MCP architecture and concepts
MCP Servers Repository	Community	2025–	GitHub repo	Reference MCP server implementations
MCP Authorization Spec	LF Projects	2025	Formal spec	OAuth 2.0 authorization for MCP

Agent-to-Agent

Source	Org	Year	Type	Why Authoritative
Agent-to-Agent Protocol (A2A)	Google	2025	GitHub repo	Google's inter-agent communication standard

Multi-Agent Systems

Source	Authors	Year	Venue	Why Authoritative
AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation	Wu et al. (Microsoft)	2024	COLM	Multi-agent conversation framework
MemGPT: Towards LLMs as Operating Systems	Packer et al.	2023	arXiv:2310.08560	OS-like memory management for agents
Agentic Memory: Learning Unified Memory Management for LLM Agents	Yu et al.	2026	arXiv:2601.01885	Unified STM + LTM memory policy

Agent Benchmarks

Source	Authors	Year	Venue	Why Authoritative
SWE-bench: Can Language Models Resolve Real-World GitHub Issues?	Jimenez et al.	2024	ICLR	Agentic coding benchmark; official leaderboard
GAIA: A Benchmark for General AI Assistants	Mialon et al.	2024	ICLR	General agent capability benchmark
WebArena: A Realistic Web Environment for Building Autonomous Agents	Zhou et al.	2024	arXiv	Web-based agent benchmark
τ-bench: A Benchmark for Tool-Agent-User Interaction	Yao et al.	2024	arXiv	Tool + user interaction benchmark

Agent Frameworks (official docs)

Source	Org	Year	Type	Why Authoritative
LangGraph	LangChain	2024–2026	Official docs	Stateful multi-actor agent framework
CrewAI	CrewAI	2024–2026	Official docs	Role-based multi-agent orchestration

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7. RAG Pipelines, Anti-Hallucination Loops

RAG Foundations

Source	Authors	Year	Venue	Why Authoritative
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks	Lewis et al. (Meta)	2020	NeurIPS	Original end-to-end RAG; 4000+ citations
Retrieval-Augmented Generation for LLMs: A Survey	Gao et al.	2024	arXiv:2312.10997	Comprehensive RAG survey (2024)
Precise Zero-Shot Dense Retrieval without Relevance Labels (HyDE)	Gao et al.	2023	ACL	Hypothesis-based retrieval
Self-RAG: Learning to Retrieve, Generate, and Critique	Asai et al.	2024	ICLR	Self-reflective retrieval
Corrective Retrieval Augmented Generation (CRAG)	Yan et al.	2024	arXiv:2401.15884	Retrieval quality evaluator + correction

Advanced Retrieval

Source	Authors	Year	Venue	Why Authoritative
From Local to Global: A Graph RAG Approach (GraphRAG)	Edge et al. (Microsoft)	2024	Microsoft Research	Graph-based RAG; enterprise adoption
RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval	Sarthi et al.	2024	ICLR	Hierarchical summarization for retrieval
Introducing Contextual Retrieval	Anthropic	2024	Anthropic Blog	Context-enhanced chunking
ColPali: Efficient Document Retrieval with Vision Language Models	Faysse et al.	2024	ICLR 2025	Vision-based document retrieval
Matryoshka Representation Learning	Kusupati et al.	2022	NeurIPS	Variable-size embeddings for flexible retrieval

RAG Evaluation

Source	Authors	Year	Venue	Why Authoritative
RAGAS: Automated Evaluation of Retrieval Augmented Generation	Es et al.	2024	EACL	Standard RAG eval framework
RAGChecker: A Fine-grained Framework for Diagnosing RAG	Ru et al.	2024	arXiv:2408.08067	Fine-grained RAG diagnostics
ClashEval: Quantifying the tug-of-war between LLM prior and evidence	Wu, Wu, Zou	2025	arXiv:2404.10198	Internal prior vs. external evidence conflict

Anti-Hallucination

Source	Authors/Org	Year	Venue	Why Authoritative
Chain-of-Verification Reduces Hallucination	Dhuliawala et al.	2023	arXiv:2309.11495	CoVe: generate → verify → revise
NeMo Guardrails: Programmable Rails for Safe LLM Applications	Rebedea et al. (NVIDIA)	2023	arXiv:2310.10501	Guardrails framework
Reducing Hallucination — Best Practices	Anthropic	2024–2026	Official docs	Provider guidance on hallucination reduction
LangSmith Tracing & Evaluation	LangChain	2024–2026	Official docs	Trace-based hallucination detection
Arize Phoenix: LLM Observability	Arize AI	2025–2026	Official docs	Open-source hallucination monitoring
W&B Weave: LLM Monitoring	Weights & Biases	2025–2026	Official docs	ML monitoring for LLM quality

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8. LLM Evaluation (Evals, Benchmarks)

LLM-as-Judge

Source	Authors	Year	Venue	Why Authoritative
Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena	Zheng et al.	2023	NeurIPS	Defines LLM-as-Judge methodology
G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment	Liu et al.	2023	arXiv:2303.16634	Chain-of-Thought evaluation with GPT-4
Large Language Models are not Fair Evaluators	Wang et al.	2023	arXiv:2305.17926	Position bias in LLM evaluation
Who Validates the Validators?	Shankar et al.	2024	arXiv:2404.12272	Meta-evaluation of LLM judges
Self-Generated Critiques Boost Reward Modeling	Yu et al.	2025	NAACL	Self-critique as reward signal
Chatbot Arena: Open Platform for Evaluating LLMs by Human Preference	Chiang et al.	2024	arXiv:2403.04132	LMSys Arena methodology
Evalica: Reliable, Reproducible Leaderboards	Ustalov	2025	COLING	Statistical significance in leaderboard ranking

Key Benchmarks

Source	Authors/Org	Year	Venue	Why Authoritative
MMLU: Measuring Massive Multitask Language Understanding	Hendrycks et al.	2021	ICLR	Most-cited LLM knowledge benchmark
BIG-bench: Beyond the Imitation Game	Srivastava et al.	2022	arXiv	204-task collaborative benchmark
GSM8K: Training Verifiers to Solve Math Word Problems	Cobbe et al. (OpenAI)	2021	NeurIPS	Standard grade-school math benchmark
MATH: Measuring Mathematical Problem Solving	Hendrycks et al.	2021	NeurIPS	Competition-level math benchmark
HumanEval: Evaluating LLMs Trained on Code	Chen et al. (OpenAI)	2021	arXiv	Code generation benchmark
SWE-bench	Jimenez et al.	2024	ICLR	Real-world GitHub issue resolution
GAIA	Mialon et al.	2024	ICLR	General AI assistant benchmark
TruthfulQA	Lin et al.	2022	ACL	Truthfulness benchmark
HellaSwag	Zellers et al.	2019	ACL	Commonsense reasoning

Evaluation Frameworks

Source	Org	Year	Type	Why Authoritative
DeepEval	Confident AI	2024–2026	GitHub repo	Unit-testing framework for LLM outputs
Promptfoo	Promptfoo	2024–2026	GitHub repo	Prompt eval + red-teaming CLI
RAGAS	VibrantLabs	2024–2026	GitHub repo	RAG-specific evaluation
Braintrust Autoevals	Braintrust	2024–2026	GitHub repo	Auto-evaluation for LLM outputs
LangSmith	LangChain	2024–2026	Official docs	Trace-based eval pipeline

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9. LLM Security (Prompt Injection, Jailbreaks, OWASP)

Standards & Taxonomies

Source	Org	Year	Type	Why Authoritative
OWASP Top 10 for LLM Applications 2025	OWASP	2025	Formal standard	Industry standard vulnerability taxonomy
MITRE ATLAS (Adversarial Threat Landscape for AI Systems)	MITRE	2024–2026	Formal framework	AI threat framework; MITRE ATT&CK companion

Prompt Injection

Source	Authors/Org	Year	Venue	Why Authoritative
Not what you've signed up for: Indirect Prompt Injection	Greshake et al.	2023	arXiv:2302.12173	Original indirect prompt injection paper
Prompt Injection Attacks and Defenses in LLM-Integrated Applications	Liu et al.	2024	arXiv:2402.02393	Comprehensive injection survey
Ignore Previous Prompt: Attack Techniques For Language Models	Schulhoff et al.	2023	NeurIPS (SoLaR)	Prompt injection taxonomy

Jailbreaks

Source	Authors/Org	Year	Venue	Why Authoritative
Universal and Transferable Adversarial Attacks (GCG)	Zou et al.	2023	arXiv:2307.15043	Greedy Coordinate Gradient — universal suffix attack
AutoDAN: Generating Stealthy Jailbreak Prompts	Liu et al.	2023	arXiv:2310.04451	Automated genetic jailbreak generation
Many-shot jailbreaking	Anthropic	2024	anthropic.com/research	Long-context jailbreak technique
The Crescendo Multi-Turn LLM Jailbreak Attack	Russinovich, Salem, Eldan (Microsoft)	2024	arXiv:2404.01833	Multi-turn escalation jailbreak
Mitigating Skeleton Key	Microsoft	2024	Security blog	Skeleton key jailbreak technique + mitigation
Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks	Andriushchenko et al.	2024	ICLR 2025	Adaptive jailbreak; SOTA attack method

Red-Teaming

Source	Authors/Org	Year	Venue	Why Authoritative
Red Teaming Language Models with Language Models	Perez et al. (Anthropic)	2022	arXiv:2202.03286	Automated LLM red-teaming
NeMo Guardrails: Programmable Rails	Rebedea et al. (NVIDIA)	2023	arXiv:2310.10501	Guardrails for safe LLM apps
PyRIT (Python Risk Identification Toolkit)	Microsoft	2024–2026	GitHub repo	Automated red-teaming framework

Provider Safety Docs

Source	Org	Year	Type	Why Authoritative
Safety & Security documentation	Anthropic	2024–2026	Official docs	Claude safety practices
GPT-5.4 System Card	OpenAI	2026	Official report	Safety evaluation for GPT-5.4
Gemini Safety documentation	Google	2025–2026	Official docs	Gemini safety features

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10. AI-Friendly Code Architecture

Foundational Principles

Source	Authors	Year	Type	Why Authoritative
Clean Code	Martin	2008	Book	Industry-standard code quality principles
Refactoring, 2nd Ed.	Fowler	2018	Book	Refactoring patterns; code improvement

LLM-Aware Architecture

Source	Authors/Org	Year	Type	Why Authoritative
AGENTS.md: A standard for AI agent project configuration	Anthropic	2026	Official spec	Standard for AI-readable project config
Rules for AI	Cursor	2025–2026	Official docs	Cursor rules for LLM-guided coding
Best practices for agentic coding	Anthropic	2025	Official docs	Coding patterns for AI agent workflows
copilot-instructions.md	GitHub	2026	Official docs	Copilot coding agent customization

Code Generation & Understanding

Source	Authors	Year	Venue	Why Authoritative
Enriching Source Code with Contextual Data for Code Completion	van Dam, Izadi, van Deursen	2023	MSR	Impact of comments/code structure on completion
Dataflow-Guided Retrieval Augmentation for Repository-Level Code Completion	Cheng, Wu, Hu	2024	ACL	Repo context graph for code completion
SpecRover: Code Intent Extraction via LLMs	Ruan, Zhang, Roychoudhury	2024	ICSE 2025	Extracting developer intent from code
Revisiting the Role of Natural Language Code Comments	Gupta et al.	2026	arXiv:2601.16661	Comments vs. LLM code understanding
Less is more: DocString compression in code generation	Yang et al.	2026	ACM TOSEM	DocString impact on generation quality
Beyond the Black Box: Survey on Theory and Mechanism of LLMs	Gan et al.	2026	arXiv:2601.02907	Meta-survey covering inference-stage practices

Prompt Pipeline Optimization

Source	Authors	Year	Venue	Why Authoritative
DSPy: Compiling Declarative Language Model Calls	Khattab et al.	2024	ICLR	Optimize LLM pipelines by metric, not manual tuning
Rethinking the Role of Demonstrations	Min et al.	2022	EMNLP	What makes in-context learning work
Calibrate Before Use	Zhao et al.	2021	ICML	LLM calibration for better performance
Large Language Models as Optimizers	Yang et al.	2024	ICLR	Iterative prompt optimization

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11. Observability (OpenTelemetry, SLO)

Standards & Specifications

Source	Org	Year	Type	Why Authoritative
Semantic Conventions for Generative AI (v1.40.0)	OpenTelemetry / CNCF	2026	Formal spec	Industry-standard GenAI observability conventions
OpenTelemetry Specification	CNCF	2019–2026	Formal spec	Distributed tracing and metrics standard

LLM-Specific Tools

Source	Org	Year	Type	Why Authoritative
OpenLLMetry	Traceloop	2025–2026	GitHub repo	OpenTelemetry-native LLM observability
Arize Phoenix	Arize AI	2025–2026	GitHub repo	Open-source LLM observability platform
LangSmith	LangChain	2024–2026	Official docs	Trace-based LLM observability + eval
W&B Weave	Weights & Biases	2025–2026	Official docs	LLM monitoring and evaluation

SLO & Reliability

Source	Authors	Year	Type	Why Authoritative
Site Reliability Engineering	Beyer et al. (Google)	2016	Book (O'Reilly)	SLI/SLO/Error Budget canon
LLMs Get Lost In Multi-Turn Conversation	Laban et al.	2025	ICLR 2026	Multi-turn reliability degradation
The Molecular Structure of Thought	Chen et al.	2026	arXiv:2601.06002	Typed traces: deep reasoning, self-reflection, self-exploration

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12. Multimodal Systems

Vision-Language

Source	Authors/Org	Year	Venue	Why Authoritative
CLIP: Learning Transferable Visual Models From Natural Language Supervision	Radford et al. (OpenAI)	2021	ICML	Contrastive vision-language pre-training; 15000+ citations
Flamingo: a Visual Language Model for Few-Shot Learning	Alayrac et al. (DeepMind)	2022	NeurIPS	Few-shot multimodal model
LLaVA: Visual Instruction Tuning	Liu et al.	2024	NeurIPS	Instruction-tuned vision-language model
Visual Instruction Tuning (LLaVA 1.5)	Liu et al.	2024	arXiv	Improved multimodal instruction tuning
Gemini: A Family of Highly Capable Multimodal Models	Gemini Team (Google)	2023	arXiv	Native multimodal architecture
Gemini 1.5: Unlocking multimodal understanding across millions of tokens	Reid et al. (Google)	2024	arXiv	Ultra-long multimodal context
GPT-4V(ision) System Card	OpenAI	2023	Official report	GPT-4 vision capabilities
Vision API docs	OpenAI	2024–2026	Official docs	OpenAI vision capabilities
Vision API docs	Anthropic	2024–2026	Official docs	Claude vision capabilities
Image Understanding docs	Google	2025–2026	Official docs	Gemini vision capabilities

Audio & Speech

Source	Org	Year	Type	Why Authoritative
Audio Understanding	Google	2025–2026	Official docs	Gemini native audio processing
Realtime API	OpenAI	2025–2026	Official docs	Speech-to-speech realtime API
Whisper: Robust Speech Recognition	Radford et al. (OpenAI)	2022	OpenAI	Speech recognition model

Document Understanding

Source	Authors	Year	Venue	Why Authoritative
ColPali: Efficient Document Retrieval with Vision Language Models	Faysse et al.	2024	ICLR 2025	Visual document retrieval via VLMs
DocTR	Mindee	2023–	GitHub repo	Open-source OCR for documents

Multimodal Hallucination

Source	Authors	Year	Venue	Why Authoritative
Evaluating Object Hallucination in Large Vision-Language Models (POPE)	Li et al.	2023	EMNLP	Vision-language hallucination benchmark
HallusionBench: An Advanced Diagnostic Suite	Guan et al.	2024	CVPR	Diagnostic vision-language hallucination

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13. Fine-Tuning, Post-Training (SFT, RLHF, DPO, LoRA)

Supervised Fine-Tuning

Source	Authors	Year	Venue	Why Authoritative
Finetuned Language Models Are Zero-Shot Learners (FLAN)	Wei et al. (Google)	2021	ICLR	Instruction tuning paradigm
Self-Instruct: Aligning LMs with Self-Generated Instructions	Wang et al.	2022	ACL	Synthetic instruction generation
Textbooks Are All You Need (Phi-1)	Gunasekar et al. (Microsoft)	2023	arXiv:2306.11644	Quality > quantity for training data
Orca: Progressive Learning from Complex Explanation Traces	Mukherjee et al. (Microsoft)	2023	arXiv:2306.02707	Learning from GPT-4 reasoning traces
LIMA: Less Is More for Alignment	Zhou et al. (Meta)	2023	arXiv:2305.11206	1000 examples enough for alignment

RLHF & Alignment

Source	Authors	Year	Venue	Why Authoritative
Training language models to follow instructions with human feedback (InstructGPT)	Ouyang et al. (OpenAI)	2022	NeurIPS	Original RLHF for instruction following
Constitutional AI: Harmlessness from AI Feedback	Bai et al. (Anthropic)	2022	arXiv:2212.08073	RLAIF — AI feedback instead of human
Scaling Laws for Reward Model Overoptimization	Gao et al.	2022	NeurIPS	Reward hacking in RLHF
DeepSeekMath: Pushing the Limits of Mathematical Reasoning	Shao et al.	2024	arXiv:2402.03300	GRPO — Group Relative Policy Optimization
DeepSeek-R1: Incentivizing Reasoning via RL	Guo et al.	2025	Nature vol. 645	Pure RL for reasoning emergence

DPO & Variants

Source	Authors	Year	Venue	Why Authoritative
Direct Preference Optimization (DPO)	Rafailov et al. (Stanford)	2023	NeurIPS	RL-free preference optimization; 2000+ citations
ORPO: Monolithic Preference Optimization without Reference Model	Hong et al.	2024	arXiv:2403.07691	Reference-free DPO alternative
KTO: Model Alignment as Prospect Theoretic Optimization	Ethayarajh et al.	2024	arXiv:2402.01306	Kahneman-Tversky prospect theory alignment
SimPO: Simple Preference Optimization with Reference-Free Reward	Meng et al.	2024	arXiv:2405.14734	Length-normalized preference optimization
RLHF Workflow: From Reward Modeling to Online RLHF	Dong et al.	2024	arXiv:2405.07863	Online vs offline RLHF comparison

Parameter-Efficient Fine-Tuning

Source	Authors	Year	Venue	Why Authoritative
LoRA: Low-Rank Adaptation of Large Language Models	Hu et al. (Microsoft)	2021	ICLR	Dominant PEFT method; 10000+ citations
QLoRA: Efficient Finetuning of Quantized LLMs	Dettmers et al.	2023	NeurIPS	LoRA + 4-bit quantization
IA3: Few-shot Parameter-Efficient Fine-Tuning	Liu et al.	2022	ACL	Inference-time PEFT via learned vectors

Knowledge Distillation

Source	Authors	Year	Venue	Why Authoritative
Distilling the Knowledge in a Neural Network	Hinton, Vinyals, Dean	2015	arXiv:1503.02531	Original distillation framework
Distilling Step-by-Step!	Hsieh et al.	2023	ACL	Reasoning distillation via CoT
MiniLLM: On-Policy Distillation of LLMs	Gu et al.	2024	ICLR	Knowledge distillation for LLMs

Provider Fine-Tuning Docs

Source	Org	Year	Type	Why Authoritative
Model Optimization (fine-tuning)	OpenAI	2024–2026	Official docs	GPT fine-tuning API
Reinforcement Fine-Tuning	OpenAI	2025–2026	Official docs	RL-based fine-tuning

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14. Design Patterns for LLM Apps

Agent Patterns (detailed in book chapters 8–10, 20)

Source	Authors	Year	Venue	Pattern
Chain-of-Thought	Wei et al.	2022	NeurIPS	Reasoning via step-by-step
Self-Consistency	Wang et al.	2023	ICLR	Majority vote over multiple reasoning paths
ReAct	Yao et al.	2023	ICLR	Interleaved reasoning + action
Reflexion	Shinn et al.	2023	NeurIPS	Self-reflection + verbal RL
Tree of Thoughts	Yao et al.	2023	NeurIPS	Tree search over reasoning paths
Graph of Thoughts	Besta et al.	2024	AAAI	Graph-structured reasoning
Chain-of-Verification	Dhuliawala et al.	2023	arXiv:2309.11495	Generate → verify → revise
RAG	Lewis et al.	2020	NeurIPS	Retrieve → augment → generate
Self-RAG	Asai et al.	2024	ICLR	Self-reflective retrieval
GraphRAG	Edge et al.	2024	Microsoft Research	Graph-based retrieval

Architectural Pattern Guides

Source	Authors/Org	Year	Type	Why Authoritative
Building Effective Agents	Anthropic	2024	Anthropic Blog	Agent design patterns: workflows → agents
LLM Powered Autonomous Agents	Weng (OpenAI)	2023	Blog	Comprehensive agent design survey
Building Production RAG	LlamaIndex	2024	Official docs	Production RAG patterns

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15. Serving & Inference

KV-Cache & Memory Management

Source	Authors	Year	Venue	Why Authoritative
Efficient Memory Management for LLM Serving with PagedAttention	Kwon et al. (vLLM)	2023	SOSP	PagedAttention — OS-inspired KV-cache; standard in vLLM
vLLM Documentation	vLLM Project	2023–2026	Official docs	Production LLM serving; disaggregated prefill
SGLang: Efficient Execution of Structured Language Model Programs	Zheng et al.	2024	arXiv	RadixAttention — prefix-aware KV-cache reuse
Prompt Cache: Modular Attention Reuse for Low-Latency Inference	Gim et al.	2024	MLSys	Prompt-level KV-cache sharing

Speculative Decoding

Source	Authors	Year	Venue	Why Authoritative
Fast Inference from Transformers via Speculative Decoding	Leviathan et al. (Google)	2023	ICML	Draft-then-verify; 2–3× speedup
Accelerating LLM Decoding with Speculative Sampling	Chen et al. (DeepMind)	2023	arXiv:2302.01318	Independent speculative sampling variant

Quantization

Source	Authors	Year	Venue	Why Authoritative
GPTQ: Accurate Post-Training Quantization for GPTs	Frantar et al.	2023	ICLR	OBQ-based weight quantization
AWQ: Activation-aware Weight Quantization	Lin et al.	2024	MLSys	Activation-aware 4-bit quantization
SmoothQuant: Accurate and Efficient Post-Training Quantization	Xiao et al.	2023	ICML	Activation + weight quantization
QLoRA: Efficient Finetuning of Quantized LLMs	Dettmers et al.	2023	NeurIPS	4-bit + PEFT
The Era of 1-bit LLMs (BitNet)	Ma et al. (Microsoft)	2024	arXiv:2402.17764	1.58-bit LLMs

Serving Frameworks

Source	Org	Year	Type	Why Authoritative
vLLM	vLLM Project (UC Berkeley)	2023–2026	GitHub repo	Most popular open-source LLM serving engine
TensorRT-LLM	NVIDIA	2023–2026	GitHub repo	NVIDIA-optimized inference
Ollama	Ollama	2024–2026	Official site	Local LLM serving for devs
SGLang	SGLang Project	2024–2026	GitHub repo	Structured generation serving

Test-Time Compute (Budget Forcing, Scaling)

Source	Authors	Year	Venue	Why Authoritative
Scaling LLM Test-Time Compute Optimally	Snell et al. (UC Berkeley, Google DeepMind)	2024	arXiv:2408.03314	Adaptive test-time compute allocation
Scaling Test-Time Compute Without Verification or RL is Suboptimal	Setlur et al.	2025	arXiv:2506.14495	Verifier necessity for test-time scaling
All Roads Lead to Likelihood: The Value of RL in Fine-Tuning	Swamy et al.	2025	arXiv:2505.14864	Solution space constrained by verifier
To CoT or not to CoT?	Sprague et al.	2025	arXiv:2503.16411	When CoT helps and when it doesn't
Chain-of-Thought Reasoning Without Prompting	Wang & Zhou	2024	arXiv:2402.10200	CoT can happen internally, not just in output

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16. Agent Orchestration, Durable Execution

Durable Execution

Source	Authors/Org	Year	Type	Why Authoritative
Sagas	Garcia-Molina & Salem	1987	ACM SIGMOD	Foundational compensating transaction pattern
Temporal: Durable Execution	Temporal Technologies	2020–2026	Official docs	Durable execution platform
Inngest: Durable Functions for AI Workflows	Inngest	2023–2026	Official docs	Serverless durable execution for AI
ADK: Long-Running Tasks	Google	2025	Official docs	Google Agent Development Kit

Agent Lifecycle & Memory

Source	Authors	Year	Venue	Why Authoritative
MemGPT: Towards LLMs as Operating Systems	Packer et al.	2023	arXiv:2310.08560	Virtual memory for agent context
Agentic Memory: Learned Unified Memory Management	Yu et al.	2026	arXiv:2601.01885	Learned STM + LTM memory policy
Generative Agents: Interactive Simulacra	Park et al.	2023	UIST	Agent memory + reflection patterns
LLMs Get Lost In Multi-Turn Conversation	Laban et al.	2025	ICLR 2026	Multi-turn drift; checkpoint summaries
Codex: Background Tasks & Sandbox Execution	OpenAI	2026	Official docs	Persistent agent execution
Claude Code: Headless & Background Mode	Anthropic	2026	Official docs	Background agent workflows

Multi-Agent Orchestration

Source	Authors/Org	Year	Type	Why Authoritative
AutoGen	Wu et al. (Microsoft)	2024	COLM	Multi-agent conversation framework
CrewAI	CrewAI	2024–2026	Official docs	Role-based orchestration
LangGraph	LangChain	2024–2026	Official docs	Graph-based stateful agent orchestration

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17. LLM Landscape 2026

Major Model Families (Official Docs)

Source	Org	Year	Type	Why Authoritative
GPT-5.4 System Card	OpenAI	2026	Official report	SOTA frontier model (May 2026)
Claude models overview (Claude Opus 4.6)	Anthropic	2026	Official docs	Frontier model with extended thinking
Claude Mythos Preview System Card	Anthropic	2026	Official report	Next-gen Claude (Project Glasswing)
Gemini API models	Google DeepMind	2026	Official docs	Gemini 3.x family
Gemma 4	Google DeepMind	2026	Official docs	Open-weight Gemma family
Llama 4	Meta AI	2025–2026	Official site	Meta open(-weight) model
DeepSeek models	DeepSeek-AI	2024–2026	GitHub + arXiv	DeepSeek-V3, DeepSeek-R1
Qwen3 / Qwen3.5 / Qwen3.6	Alibaba	2025–2026	GitHub + blog	Qwen open-weight family
GLM-5.1	Zhipu AI / Z.ai	2026	Official site	Agentic-optimized model
Grok 4.20	xAI	2026	Official docs	Grok family
MiniMax-M2.7	MiniMax	2026	Official site	Self-evolution claims

Reasoning Models

Source	Authors/Org	Year	Venue	Why Authoritative
DeepSeek-R1	Guo et al. / DeepSeek-AI	2025	Nature vol. 645	Pure RL for reasoning emergence
o3 System Card	OpenAI	2025	Official report	Frontier reasoning model
GPT-5.4 System Card	OpenAI	2026	Official report	Reasoning + tool use integration
Qwen3.6-Plus: Towards Real World Agents	Qwen Team	2026	Research blog	Agentic reasoning capabilities
Training LLMs to Reason in a Continuous Latent Space (Coconut)	Hao et al.	2025	arXiv:2412.06769	Continuous latent reasoning

MoE & Hybrid Architecture

Source	Authors/Org	Year	Venue	Why Authoritative
Mixtral of Experts	Mistral AI	2024	arXiv:2401.04088	Production MoE (8×7B)
DeepSeek-V3 Technical Report	DeepSeek-AI	2024	arXiv:2412.19437	671B MoE production model
Jamba 2	AI21 Labs	2026	Official blog	Hybrid SSM-Transformer-MoE, 256K
Transformers are SSMs (Mamba-2)	Dao & Gu	2024	ICML	Unified hybrid framework

SLM & Edge

Source	Authors/Org	Year	Venue	Why Authoritative
Phi-4 Technical Report	Microsoft	2025	arXiv	MSR's small language model family
SmolLM3	HuggingFace	2025	HuggingFace	Open lightweight LM (3B)
Qwen3.5-0.8B	Alibaba / Qwen Team	2026	HuggingFace	Sub-1B capable model
The Era of 1-bit LLMs (BitNet)	Ma et al. (Microsoft)	2024	arXiv:2402.17764	1.58-bit extreme compression

Emerging: Diffusion LLM

Source	Authors	Year	Venue	Why Authoritative
MDLM	Sahoo et al.	2024	NeurIPS	Masked diffusion for language
SEDD	Lou et al.	2024	ICML	Score entropy discrete diffusion
Mercury	Inception Labs	2025–2026	Official site	First production diffusion LLM
LLaDA	Nie et al.	2025	arXiv:2502.09992	8B diffusion matching LLaMA3

MCP Ecosystem

Source	Org	Year	Type	Why Authoritative
MCP Spec (v2025-11-25)	LF Projects / Anthropic	2024–2025	Formal spec	Canonical protocol specification
MCP Connector (Anthropic)	Anthropic	2025–2026	Official docs	Native MCP client in Claude
Tools, Connectors, and MCP	OpenAI	2025–2026	Official docs	MCP support in Responses API
A2A Protocol	Google	2025	GitHub repo	Inter-agent protocol

Model Technical Reports (Official)

Source	Authors/Org	Year	Type	Why Authoritative
GPT-4 Technical Report	OpenAI	2023	arXiv:2303.08774	GPT-4 architecture overview
The Claude 3 Model Family: Opus, Sonnet, Haiku	Anthropic	2024	Anthropic	Claude 3 family
The Llama 3 Herd of Models	Meta AI	2024	arXiv:2407.21783	Llama 3 family (8B, 70B, 405B)
Gemma 2: Improving Open Language Models at a Practical Size	Google DeepMind	2024	arXiv:2408.00118	Gemma 2 family
GLM-5: from Vibe Coding to Agentic Engineering	Du et al. (Zhipu)	2026	arXiv:2602.15763	GLM-5 technical report

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Key Benchmark Official Pages

Benchmark	Official URL	What It Measures
LMSys Chatbot Arena	https://chat.lmsys.org/	Human preference ELO ranking
MMLU	https://github.com/hendrycks/test	Multi-task language understanding
SWE-bench	https://www.swebench.com/	Real GitHub issue resolution
GAIA	https://huggingface.co/gaia-benchmark	General AI assistant capabilities
HumanEval	https://github.com/openai/human-eval	Code generation
GSM8K	https://github.com/openai/grade-school-math	Grade-school math
MATH	https://github.com/hendrycks/math	Competition math
TruthfulQA	https://github.com/sylinrl/TruthfulQA	Truthfulness
BIG-bench	https://github.com/google/BIG-bench	204 diverse tasks
MT-Bench	https://github.com/lm-sys/FastChat	Multi-turn conversation
HellaSwag	https://rowanzellers.com/hellaswag/	Commonsense reasoning
SimpleQA	https://openai.com/index/simpleqa/	Short-form factuality
HELMET	https://github.com/princeton-nlp/HELMET	Long-context evaluation

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Notes

• Venue abbreviations: NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, AAAI, TACL, TMLR, SOSP, MLSys, COLM, MSR, CVPR, EACL, COLING, SIGMOD, SOSP.
• Official docs include Anthropic Platform docs, OpenAI API docs, Google AI docs, and official GitHub repos.
• "Official blog" refers only to research blogs from OpenAI, Anthropic, Google DeepMind, Meta AI, Microsoft Research — not personal blogs.
• Sources already cited in the book's chapter ## Источники sections are all included above, with additions for completeness.
• For fact-checking: verify claims against the most recent version of official docs (Anthropic Platform, OpenAI API, Google AI) as they update frequently.