--- id: "/tags/data-datasets/page/3/" title: "Data Datasets · page 3" url: "https://skillissue.dev/tags/data-datasets/page/3/" --- # Data Datasets [Beginner](/levels/beginner/index.md) [Intermediate](/levels/intermediate/index.md) [Advanced](/levels/advanced/index.md) [Expert](/levels/expert/index.md) 88 resources · page 3 of 3 - ### [HANDBOOK.md Benchmark (Surge AI)](/context-engineering/retrieval-and-rag/surge-ai-handbook-md-benchmark/index.md) by [Surge AI](https://surgehq.ai/) Surge AI post on HANDBOOK.md, a benchmark testing whether agents follow long company policy handbooks. Intermediate learning_resource blog US en - ### [HellaSwag or HellaBad? (Surge AI)](/context-engineering/retrieval-and-rag/surge-ai-hellaswag-or-hellabad-36-contains-errors/index.md) by [Surge AI](https://surgehq.ai/) Surge AI audit reporting errors in 36% of HellaSwag benchmark rows, with examples. Intermediate learning_resource blog US en - ### [The Pile](/context-engineering/retrieval-and-rag/the-pile/index.md) by [Leo Gao et al. (EleutherAI)](https://www.eleuther.ai/) arXiv paper (2021) "The Pile: An 800GB Dataset of Diverse Text for Language Modeling", describing its 22 component sources and construction. Intermediate learning_resource paper US en - ### [How Shopify and Toloka built a ground-truth flywheel](/context-engineering/retrieval-and-rag/toloka-shopify-toloka-ground-truth-flywheel/index.md) by [Toloka](https://toloka.ai/) Toloka case study on building a human-labelled ground-truth loop with Shopify to keep skill agents accurate. Intermediate learning_resource guide Netherlands (RU-origin) en - ### [Writing tests with GitHub Copilot](/context-engineering/retrieval-and-rag/unit-and-integration-test-generation-writing-tests-with-github-copilot-verified-/index.md) by [GitHub](https://github.com/) GitHub tutorial on generating unit and integration tests with GitHub Copilot. Intermediate learning_resource guide US en - ### [Ai2 model cards and datasets](/context-engineering/retrieval-and-rag/ai2-model-cards-and-datasets/index.md) by [Ai2](https://huggingface.co/allenai) Ai2's Hugging Face organisation page listing its model checkpoints, model cards and datasets, including OLMo. Advanced learning_resource docs US en - ### [Alibi Detect](/context-engineering/retrieval-and-rag/alibi-detect/index.md) by [Seldon](https://www.seldon.io/) Alibi Detect documentation: Python library for outlier, adversarial and data-drift detection in ML systems. Advanced learning_resource docs UK/global en - ### [Cleanlab documentation](/context-engineering/retrieval-and-rag/cleanlab-documentation/index.md) by [Cleanlab](https://cleanlab.ai/) Cleanlab documentation: open-source library for finding label errors and data issues in ML datasets. Advanced learning_resource docs US en - ### [Datasheets for Datasets](/context-engineering/retrieval-and-rag/datasheets-for-datasets/index.md) by [Timnit Gebru et al. (Microsoft Research)](https://www.microsoft.com/en-us/research/) Microsoft Research page for Datasheets for Datasets, proposing standard documentation for ML datasets. Advanced learning_resource paper United States / international collaboration en - ### [LanceDB documentation](/context-engineering/retrieval-and-rag/lancedb-documentation/index.md) by [LanceDB](https://lancedb.com/) LanceDB documentation: multimodal lakehouse and vector database for AI data, with versioned tables and retrieval. Advanced learning_resource docs US en - ### [LLM-jp corpora (GitLab)](/context-engineering/retrieval-and-rag/llm-jp-corpora-gitlab/index.md) by [LLM-jp (National Institute of Informatics)](https://llm-jp.nii.ac.jp/) LLM-jp datasets on the NII GitLab: open Japanese pretraining corpora. Advanced learning_resource docs Japan ja - ### [NeurIPS paper checklist](/context-engineering/retrieval-and-rag/neurips-paper-checklist/index.md) by [NeurIPS Foundation](https://neurips.cc/) NeurIPS paper checklist covering assumptions, limitations, experimental details, reproducibility and broader impacts. Advanced learning_resource guide Global en - ### [Qdrant documentation](/context-engineering/retrieval-and-rag/qdrant-documentation/index.md) by [Qdrant](https://qdrant.tech/) Qdrant documentation: vector search engine with quickstarts, filtering, hybrid search and deployment guides. Advanced learning_resource docs Germany en - ### [Retrieval-Augmented Generation](/context-engineering/retrieval-and-rag/retrieval-augmented-generation/index.md) by [Patrick Lewis et al. (Facebook AI Research)](https://ai.meta.com/) arXiv paper (2020) "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks", introducing retrieval-augmented generation (RAG). Advanced learning_resource paper US; UK en - ### [RL environments for LLM agents: Design, rewards, and validation (Snorkel)](/context-engineering/retrieval-and-rag/snorkel-rl-environments-for-llm-agents-design-rewards-validation/index.md) by [Snorkel AI](https://snorkel.ai/) Snorkel AI post on designing RL environments for LLM agents: state, actions, rewards and validation. Advanced learning_resource blog US en - ### [Partial Credit in RL: When It Opposes Completion (Snorkel)](/context-engineering/retrieval-and-rag/snorkel-when-partial-credit-opposes-completion/index.md) by [Snorkel AI](https://snorkel.ai/) Snorkel AI post on how partial-credit rewards in reinforcement learning can work against task completion. Advanced learning_resource blog US en - ### [Training Compute-Optimal Large Language Models](/context-engineering/retrieval-and-rag/training-compute-optimal-large-language-models/index.md) by [Jordan Hoffmann et al. (DeepMind)](https://deepmind.google/) arXiv paper (2022) "Training Compute-Optimal Large Language Models", describing Chinchilla and compute-optimal model size versus training tokens. Advanced learning_resource paper UK en - ### [Weaviate documentation](/context-engineering/retrieval-and-rag/weaviate-documentation/index.md) by [Weaviate](https://weaviate.io/) Weaviate documentation: open-source vector database with guides on indexing, search and RAG pipelines. Advanced learning_resource docs Netherlands en - ### [Synthetic Data in Investment Management (CFA Institute)](/context-engineering/retrieval-and-rag/cfa-institute-synthetic-data-in-investment-management-2025/index.md) by [CFA Institute Research and Policy Center](https://rpc.cfainstitute.org/) CFA Institute Research and Policy Center report (2025) on synthetic data in investment management. Expert learning_resource paper Global en - ### [DataComp / DCLM](/context-engineering/retrieval-and-rag/datacomp-dclm/index.md) by [DataComp team (University of Washington and others)](https://www.datacomp.ai/) DataComp site: data-centric benchmarks for building better training datasets for CLIP models and language models (DCLM). Expert learning_resource docs US en - ### [DCLM paper](/context-engineering/retrieval-and-rag/dclm-paper/index.md) by [Jeffrey Li et al. (University of Washington)](https://www.washington.edu/) arXiv paper (2024) introducing DataComp-LM (DCLM), a testbed for curating language model training sets. Expert learning_resource paper US en - ### [Microsoft GraphRAG](/context-engineering/retrieval-and-rag/microsoft-graphrag/index.md) by [Microsoft](https://opensource.microsoft.com) Microsoft GraphRAG documentation: RAG approach that builds an LLM-generated knowledge graph for global summarisation queries. Expert learning_resource docs US en - ### [Do people click on links in Google AI summaries? (Pew Research Center)](/context-engineering/retrieval-and-rag/pew-research-google-users-less-likely-to-click-links-when-an-ai-summary-appears-/index.md) by [Pew Research Center](https://pewresearch.org/) Pew Research short read on Google users clicking fewer links when an AI summary appears. Expert learning_resource paper US en - ### [Yandex ШАД (School of Data Analysis)](/context-engineering/retrieval-and-rag/yandex-school-of-data-analysis/index.md) by [Yandex School of Data Analysis](https://shad.yandex.ru/) Yandex School of Data Analysis: free two-year Russian programme in ML, data analysis and engineering. Expert learning_resource course Russia ru [Previous page](/tags/data-datasets/page/2/index.md) [Plain-text Markdown copy](/tags/data-datasets/page/3/index.md)