datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
contextual_testCheck out the paper.
SWE-bench_Pro
Dataset Summary
SWE-Bench Pro is a challenging, enterprise-level dataset for testing agent ability on long-horizon software engineering tasks.
Paper: https://static.scale.com/uploads/654197dc94d34f66c0f5184e/SWEAP_Eval_Scale%20(9).pdf
See the related evaluation Github: https://github.com/scaleapi/SWE-bench_Pro-os
Dataset Structure
We follow SWE-Bench Verified (https://huggingface.co/datasets/SWE-bench/SWE-bench_Verified) in terms of dataset structure, with several… See the full description on the dataset page: https://huggingface.co/datasets/Contextbench/SWE-bench_Pro.movie_reviews_with_context_drift
Dataset Card for reviews_with_drift
Dataset Description
Dataset Summary
This dataset was crafted to be used in our tutorial [Link to the tutorial when ready]. It consists on a large Movie Review Dataset mixed with some reviews from a Hotel Review Dataset. The training/validation set are purely obtained from the Movie Review Dataset while the production set is mixed. Some other features have been added (age, gender, context) as well as a made up timestamp… See the full description on the dataset page: https://huggingface.co/datasets/arize-ai/movie_reviews_with_context_drift.empathetic-dialogues-contexts
Dataset Description
This is a dataset of emotional contexts that was retrieved from the original EmpatheticDialogues (ED) dataset. Respondents were asked to describe an event that was associated with a particular emotion label (i.e. p(event|emotion).
There are 32 emotion labels in total.
There are 19209, 2756, and 2542 instances of emotional descriptions in the train, valid, and test set, respectively.
context-ucurve-coding-agents
Context U-curve: 36 coding-agent runs under six context-clearing policies
How often should an LLM coding agent's context be cleared? This dataset holds every run behind the report
"Clear Every Third Task: A Measured U-Curve in the Context Economy of Coding Agents"
(Evgenii Arsentev, 2026; corrected version 1.2, DOI 10.5281/zenodo.22759217; version 1.0: DOI 10.5281/zenodo.22699668).
A fixed suite of twelve programming tasks was run under six session-length policies — a fresh… See the full description on the dataset page: https://huggingface.co/datasets/arsentev-ai/context-ucurve-coding-agents.deepseek-1m-context-benchmark
DeepSeek 1M Context Benchmark
This dataset is the publication-safe measurement release for DeepSeek 1M Context Benchmark: Retrieval Accuracy, Latency, and Cost, version v1.0.0. It contains 344 sanitized terminal API records produced by the frozen protocol deepseek-v4-long-context-retrieval-v1.1.0 during a bounded run from 2026-08-06T20:17:02.706Z through 2026-08-07T00:07:44.737Z.
The study compared deepseek-v4-flash and deepseek-v4-pro on deterministic synthetic English… See the full description on the dataset page: https://huggingface.co/datasets/chatdeepai/deepseek-1m-context-benchmark.p2026-002-quantization-context-compression-results
Deployed Quantization Tier and Lossy Context Compression in Extractive QA
This result dataset mirrors the version-1.0.0 reproducibility artifact:
10.5281/zenodo.22847291.
The versioned report and full replication sources
are maintained together in the research-artifacts repository. Cite the exact
Zenodo version for the frozen evidence; this Hugging Face copy is a discovery
mirror.
Matthew Schwartz — ORCID 0009-0009-4171-7247
This dataset is the aggregate-only evidence for "No… See the full description on the dataset page: https://huggingface.co/datasets/mv1137/p2026-002-quantization-context-compression-results.contextual-sensitive-data
Towards Contextual Sensitive Data Detection
This dataset includes tables with sensitivity annotations that were used to train and evaluate methods for detecting contextual sensitive data. It accompanies the paper "Towards Contextual Sensitive Data Detection".
Links:
Paper: https://huggingface.co/papers/2512.04120
Code: https://github.com/trl-lab/sensitive-data-detection
Sample Usage
The GitHub repository provides scripts for running inference and fine-tuning using… See the full description on the dataset page: https://huggingface.co/datasets/trl-lab/contextual-sensitive-data.model-context-windows
LLM Context Windows — 206 models
Context-window sizes for 206 ready models served by the Qubax AI API (OpenAI-compatible), exported from the public /v1/models endpoint.
Columns
Column
Description
model_id
API model identifier
model_name
Display name
context_window_tokens
Max context window (tokens)
max_output_tokens
Max output (tokens, where published)
source
Provenance
Notes
License: CC0 1.0 (public domain) — use freely in… See the full description on the dataset page: https://huggingface.co/datasets/QubaxAI/model-context-windows.Selective-Context-Gemma3-12B-resultsvietnamese-poem-contextcontext-aware-arabic-to-english-model-with-register
Context-Aware Arabic Dialect Translation Dataset
This repository contains the dataset and code for the paper "Context-Aware Dialectal Arabic Machine Translation with Interactive Region and Register Selection" (Anonymous Submission).
Contents
context_aware_en_ar_v2.ipynb: The main Google Colab notebook used for training and evaluation.
balanced_dataset_ready.csv: The full augmented dataset (57,600 sentence pairs) produced by our RBDA pipeline.
train_dataset.csv: The… See the full description on the dataset page: https://huggingface.co/datasets/Arabic-NLP-2026/context-aware-arabic-to-english-model-with-register.citation_context
Citation Contexts for Scientific Evidence Retrieval
Dataset Description
This dataset contains 9,920 citation occurrences extracted from English-language scientific papers. Each row represents one occurrence of a citation in a source paper and links it to the cited paper. It provides four increasingly broad representations of the citation context:
the sentence containing the citation (context_c1_sentence);
the complete source paragraph (context_c2_paragraph);
a… See the full description on the dataset page: https://huggingface.co/datasets/sanaa-11/citation_context.context-economy-agent-sessions
Context economy: modeled cost of 722 coding-agent sessions
Per-session data behind the report "The Context Economy of Agentic LLM Sessions: Where the Money Actually Goes"
(Evgenii Arsentev, 2026; corrected version 1.1, DOI 10.5281/zenodo.22759216).
Report page: https://arsentev.ai/research/context-economy-of-agentic-llm-sessions
What is in the file
sessions.csv has one row per session, 722 rows, sorted by modeled cost:
column
meaning
session_id… See the full description on the dataset page: https://huggingface.co/datasets/arsentev-ai/context-economy-agent-sessions.GA_Long_Context_Jailbreak_Benchmark
GA Long Context Bench
A benchmark of 1500 multi-turn conversations designed to stress guardrails in long contexts. Each dialog pairs a serialized agent trace with optional prompt injections or per-policy adjudications. Half of the rows embed malicious content deep inside long instructions, enabling evaluation of long-context systems.
Accompanying guardrail releases: GA Guard Core and GA Guard Lite. Check out public benchmarks and results in our blogpost.
[!Note]
Disclaimer: This… See the full description on the dataset page: https://huggingface.co/datasets/GeneralAnalysis/GA_Long_Context_Jailbreak_Benchmark.taiwan-conversation-context-100-domains
Taiwan Conversation Context 100 Domains
Dataset Description
Taiwan Conversation Context 100 Domains 是一套以台灣日常生活情境為核心設計的雙人對話文本資料集。
本資料集包含 100 個生活領域，每個領域各有 12,000 筆對話資料，總計約 1,200,000 筆對話樣本。每筆資料皆為雙人對話格式，包含 [A][B][A][B][A][B][A][B] 共 8 個發言，也就是 4 輪來回對話。
資料以繁體中文撰寫，並針對台灣在地語境設計，適合用於：
語音生成資料前處理
Text-to-Speech, TTS
Spoken Dialogue Generation
Conversational AI
Customer Service Dialogue Modeling
Role-play Dialogue Dataset
台灣繁體中文語音模型訓練
生活情境問答模型訓練
對話式 AI 助理訓練
RAG / Agent 測試資料… See the full description on the dataset page: https://huggingface.co/datasets/Ethan615/taiwan-conversation-context-100-domains.frontier-blindspots-islamic-context
Blind Spots of Frontier Models: Islamic & Cultural Context
Author: Arafat Lakhani
Model evaluated: Qwen/Qwen2.5-3B-Instruct (3B parameters, ungated, runs on a free Colab T4)
Artifacts in this repo: islamic_blindspot_eval_seed.csv (the evaluation set I built), results_qwen2.5-3b_GRADED.csv (every model output with my hand grading), results_by_category.png (summary chart), and fatima_blindspot_colab.ipynb (the notebook I ran).
Q1. The blind spot (in my own words)… See the full description on the dataset page: https://huggingface.co/datasets/Xevelyn/frontier-blindspots-islamic-context.contextual_valCheck out the paper.
Financial_Context_DatasetThis dataset contains over 50,000 samples of user financial queries paired with their corresponding structured data requests (context). It was created to facilitate the creation of the Financial Agent LLM for accurate data extraction and query answering.
How to load the Dataset
You can load the dataset using the code below:
from datasets import load_dataset
ds = load_dataset("Chaitanya14/Financial_Context_Dataset")
Dataset Construction
Diverse Query Sources… See the full description on the dataset page: https://huggingface.co/datasets/Chaitanya14/Financial_Context_Dataset.Context-Aware-Repository-Prompt-Injection
Overview
This dataset is designed for training and evaluating AI security scanners that detect repository-aware prompt injection attacks in software development and code-assistant environments.
Repository-aware prompt injections are malicious instructions embedded in code repositories, documentation, comments, configuration files, issue trackers, or other project artifacts that attempt to manipulate an AI system's behavior, override its instructions, exfiltrate sensitive… See the full description on the dataset page: https://huggingface.co/datasets/ShieldX/Context-Aware-Repository-Prompt-Injection.Synthetic-Context-Conversations
Synthetic-Context-Conversations
Overview
The Synthetic-Context-Conversations dataset is a collection of synthetic conversations designed to simulate empathetic and context-rich dialogues. It is particularly useful for tasks such as text generation, summarization, and question answering. The dataset is available in English and contains between 10,000 to 100,000 entries.
Dataset Details
Modalities: Text
Languages: English
Size: 10K-100K
Formats: Parquet
License:… See the full description on the dataset page: https://huggingface.co/datasets/prithivMLmods/Synthetic-Context-Conversations.sql-spider-kaggledbqa-with-contextreality-check-on-context-utilisation
Dataset card for the dataset used in "A Reality Check on Context Utilisation for Retrieval-Augmented Generation"
Dataset Details
This dataset was used for the analysis and plots in the paper "A Reality Check on Context Utilisation for Retrieval-Augmented Generation". More details on the dataset can be found in the paper.
Dataset Description
The dataset contains samples from CounterFact (Meng et al. 2022), ConflictQA (Xie et al. 2024), and DRUID with… See the full description on the dataset page: https://huggingface.co/datasets/copenlu/reality-check-on-context-utilisation.patient-risk-benefit-context-v0.1
What this dataset tests
Patient materials must show tradeoffs.
Benefit without harm misleads.
Why it exists
Patient-facing text often sells.
Harms go missing.
This set checks whether risk and benefit context stays intact.
Data format
Each row contains
benefit_evidence
harm_evidence
patient_material
context_pressure
constraints
failure_modes_to_avoid
target_behaviors
gold_checklist
Feed the model
benefit_evidence
harm_evidence… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/patient-risk-benefit-context-v0.1.databricks-dolly-15k-context-3k-ragcontext_toxicityhttps://github.com/ipavlopoulos/context_toxicity/
@inproceedings{xenos-etal-2021-context,
title = "Context Sensitivity Estimation in Toxicity Detection",
author = "Xenos, Alexandros and
Pavlopoulos, John and
Androutsopoulos, Ion",
booktitle = "Proceedings of the 5th Workshop on Online Abuse and Harms (WOAH 2021)",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url =… See the full description on the dataset page: https://huggingface.co/datasets/tasksource/context_toxicity.Multilingual_Customer_Support_Intent_Dataset_for_Indian_Contexts
Multilingual Customer Support Intent Dataset for Indian Contexts
Overview
This dataset contains multilingual customer support queries across Indian contexts including ecommerce, banking, telecom, travel, and technology.
Features
Multilingual: English, Hindi, Hinglish, Punjabi
Intent labeled (refund, payment_issue, account_issue, delivery_issue, complaint)
Real-world customer queries
Use Cases
Customer support chatbots
Intent classification models… See the full description on the dataset page: https://huggingface.co/datasets/karanverma19/Multilingual_Customer_Support_Intent_Dataset_for_Indian_Contexts.Selective-Context-Llama3.1-8B-resultsContextual_Response_Evaluation_for_ESL_and_ASD_Support
Dataset Card for "Contextual Response Evaluation for ESL and ASD Support💜💬🌐""
Dataset Description 📖
Dataset Summary 📝
Curated by Eric Soderquist, this dataset is a collection of English prompts and responses generated by the Phi-2 model, designed to evaluate and improve NLP models for supporting ESL (English as a Second Language) and ASD (Autism Spectrum Disorder) user bases. Each prompt is paired with multiple AI-generated responses and evaluated using a… See the full description on the dataset page: https://huggingface.co/datasets/yunjaeys/Contextual_Response_Evaluation_for_ESL_and_ASD_Support.humanoid-context-aware-commands
Humanoid Context-Aware Commands
This dataset contains structured, context-aware natural language commands for humanoid robot AI training.
Description
The dataset is designed to help humanoid robots understand intent, context, and action categories from human instructions.
Use Cases
NLP command understanding
Humanoid robot control
AI agent instruction following
Robotics simulation environments
Format
CSV with fields:
text: natural language command… See the full description on the dataset page: https://huggingface.co/datasets/ariefansclub/humanoid-context-aware-commands.