Context Engineering for advanced learners
49 resources · page 2 of 2
Ai2 model cards and datasets
Creator not supplied; see original source.
Ai2's Hugging Face organisation page listing its model checkpoints, model cards and datasets, including OLMo.
Alibi Detect
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Alibi Detect documentation: Python library for outlier, adversarial and data-drift detection in ML systems.
Effective harnesses for long-running agents
by Anthropic
Harness design for agents that work across many context windows.
Context Rot: How Increasing Input Tokens Impacts LLM Performance
by Chroma
Measures how output quality drops as input length grows.
Cleanlab documentation
Creator not supplied; see original source.
Cleanlab documentation: open-source library for finding label errors and data issues in ML datasets.
Datasheets for Datasets
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Microsoft Research page for Datasheets for Datasets, proposing standard documentation for ML datasets.
LanceDB documentation
Creator not supplied; see original source.
LanceDB documentation: multimodal lakehouse and vector database for AI data, with versioned tables and retrieval.
LLM-jp corpora (GitLab)
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LLM-jp datasets on the NII GitLab: open Japanese pretraining corpora.
A Survey of Context Engineering for LLMs (arXiv 2507.13334)
by Mei et al. (Chinese Academy of Sciences et al.)
A research map of retrieval, context processing and memory systems.
NeurIPS paper checklist
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NeurIPS paper checklist covering assumptions, limitations, experimental details, reproducibility and broader impacts.
RAG Techniques
by Nir Diamant and contributors
Compare retrieval designs through code-oriented examples.
Qdrant documentation
Creator not supplied; see original source.
Qdrant documentation: vector search engine with quickstarts, filtering, hybrid search and deployment guides.
Retrieval-Augmented Generation
Creator not supplied; see original source.
arXiv paper (2020) "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks", introducing retrieval-augmented generation (RAG).
RL environments for LLM agents: Design, rewards, and validation (Snorkel)
Creator not supplied; see original source.
Snorkel AI post on designing RL environments for LLM agents: state, actions, rewards and validation.
Partial Credit in RL: When It Opposes Completion (Snorkel)
Creator not supplied; see original source.
Snorkel AI post on how partial-credit rewards in reinforcement learning can work against task completion.
Training Compute-Optimal Large Language Models
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arXiv paper (2022) "Training Compute-Optimal Large Language Models", describing Chinchilla and compute-optimal model size versus training tokens.
Weaviate documentation
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Weaviate documentation: open-source vector database with guides on indexing, search and RAG pipelines.