datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
agent-llm-traces-v2
Exgentic Agent LLM Traces v2 — Agent Chat Only
OpenTelemetry-shaped execution traces for 10,057 agent runs across 6 benchmarks (AppWorld, SWE-bench, BrowseCompPlus, τ²-bench Airline/Retail/Telecom), filtered to the agent under test's chat-only LLM calls. This is the dataset for replay testing, behavioral analysis, or any task where you care about what the benchmarked model actually did — not the eval scaffolding around it.
This v2 release expands upon Exgentic/agent-llm-traces… See the full description on the dataset page: https://huggingface.co/datasets/Exgentic/agent-llm-traces-v2.agent-llm-traces
Multi-Benchmark LLM Agent Traces
A comprehensive dataset of OpenTelemetry traces capturing LLM inference behavior across multiple agent frameworks, benchmarks, and model providers. This dataset enables research into LLM performance analysis, agent behavior patterns, and inference optimization.
Collected by Exgentic - A platform for LLM observability and performance optimization.
Dataset Overview
This dataset contains 1,781 execution traces capturing detailed agent… See the full description on the dataset page: https://huggingface.co/datasets/Exgentic/agent-llm-traces.CriticBench
Dataset Card for Dataset Name
CriticBench is a comprehensive benchmark designed to assess LLMs' abilities to generate, critique/discriminate and correct reasoning across a variety of tasks. CriticBench encompasses five reasoning domains: mathematical, commonsense, symbolic, coding, and algorithmic. It compiles 15 datasets and incorporates responses from three LLM families.
Dataset Details
Dataset Description
Curated by: THU
Funded by [optional]: [More… See the full description on the dataset page: https://huggingface.co/datasets/llm-agents/CriticBench.agentic-llm-pretraining-1.7b
Agentic LLM Pretraining Dataset
A pretraining corpus for small language models (1-3B parameters) optimized for agentic tasks. The corpus emphasizes learning to comprehend language, reason, follow instructions, and use tools over memorizing factual knowledge — the assumption is that domain knowledge will be provided at runtime via RAG. The idea is that this could enable much smaller pretraining corpora by omitting the large volumes of text typically needed to memorize facts.… See the full description on the dataset page: https://huggingface.co/datasets/visionscaper/agentic-llm-pretraining-1.7b.agent-llm-traces
Multi-Benchmark LLM Agent Traces
A comprehensive dataset of OpenTelemetry traces capturing LLM inference behavior across multiple agent frameworks, benchmarks, and model providers. This dataset enables research into LLM performance analysis, agent behavior patterns, and inference optimization.
Collected by Exgentic - A platform for LLM observability and performance optimization.
Dataset Overview
This dataset contains 1,781 execution traces capturing detailed agent… See the full description on the dataset page: https://huggingface.co/datasets/DiscoPosse/agent-llm-traces.aiwolf-nlp-agent-llm
AIWolfDial 2026 Power Play Evaluation
Public data release: 2026-09-14. This dataset is available at synonym/aiwolf-nlp-agent-llm, with the snapshot tag release-20260914. The matching code distribution is 1.0.0-rc.3, commit d427dc299bacf4eb4cb41c114c8af476b71ac7ed. The code distribution uses a single root commit; this dataset is separate and is not included in that repository. Paper publication identifiers are still pending. The dataset is distributed under the MIT license in… See the full description on the dataset page: https://huggingface.co/datasets/synonym/aiwolf-nlp-agent-llm.llm-agent-harness-reliability-next-prime
LLM Next Prime Harness Dataset
This dataset contains raw observations from an experiment studying how the agent harness affects reliability when an LLM has access to a deterministic tool.
The task is deliberately simple and objectively verifiable:
What is the smallest prime number that is strictly greater than n?
The deterministic tool computes the correct answer with a local Python next_prime(n) function. The experiment asks whether failures come from the model, the provider… See the full description on the dataset page: https://huggingface.co/datasets/hoololi/llm-agent-harness-reliability-next-prime.llm-rag-agent-papers
llm-rag-agent-papers
Research papers on LLM, RAG, and AI Agents - Knowledge base for RAG pipeline
Dataset Structure
This dataset contains three subsets:
llm: Large Language Model related content
rag: Retrieval-Augmented Generation related content
agent: AI Agent related content
Usage
from datasets import load_dataset
# Load all subsets
dataset = load_dataset("GXMZU/llm-rag-agent-papers")
# Load specific subset
llm_data =… See the full description on the dataset page: https://huggingface.co/datasets/GXMZU/llm-rag-agent-papers.automl_llm_agent_m3
AutoML-LLM Agent Module 3 Benchmark
This dataset contains the Module 3 benchmark for evaluating an assistant that converts AutoGluon training evidence and a surrogate XAI report into a decision-oriented report for a domain expert without AI training.
The repository is scoped to Module 3 only. Its seven cases reuse the processed datasets and reference configurations established by Modules 1 and 2.
Tables
module3_cases: one row per evaluation case, with canonical… See the full description on the dataset page: https://huggingface.co/datasets/tecnologiactc/automl_llm_agent_m3.Estwld-empathetic_dialogues_llmReformatted version of Estwld/empathetic_dialogues_llm.
Changes:
Added a random system prompt for the AI to be empathetic
Truncated conversations that don't end with the AI's turn
Removed extra fields not needed in the conversation
Limitations:
The dialogues aren't very long
No background info for the user and AI
English only
llm-agent-papers
LLM Agent & Tool-Use Papers — FineSet
A research-paper dataset on LLM Agent & Tool-Use Papers, assembled, deduplicated, and quality-scored by
FineSet from arXiv and Semantic Scholar.
📸 This is a dated snapshot — generated 2026-06-12.
It is not auto-updated. Research on LLM Agent & Tool-Use Papers moves fast — new papers land on arXiv every
week. Want this same dataset refreshed daily, on a topic you choose? See the bottom. ↓
Why this dataset
Quality-scored:… See the full description on the dataset page: https://huggingface.co/datasets/fineset-io/llm-agent-papers.llm-rag-agent-blogs
llm-rag-agent-blogs
Technical blogs on LLM, RAG, and AI Agents - Knowledge base for RAG pipeline
Dataset Structure
This dataset contains three subsets:
llm: Large Language Model related content
rag: Retrieval-Augmented Generation related content
agent: AI Agent related content
Usage
from datasets import load_dataset
# Load all subsets
dataset = load_dataset("GXMZU/llm-rag-agent-blogs")
# Load specific subset
llm_data =… See the full description on the dataset page: https://huggingface.co/datasets/GXMZU/llm-rag-agent-blogs.agentic-llm-pretraining-1.7b-tokenized-qwen3-4k
Agentic LLM Pretraining Dataset - Tokenized (Qwen3, 4K context)
Pre-tokenized version of visionscaper/agentic-llm-pretraining-1.7b for pre-training small language models for agentic AI use cases.
Overview
Property
Value
Source dataset
visionscaper/agentic-llm-pretraining-1.7b
Tokenizer
Qwen/Qwen3-1.7B
Context length
4,096 tokens
EOD token
<|endoftext|> (ID 151643)
Token dtype
uint32
Total samples
375,384
Total tokens
~1.54 billion
Storage
~5.8 GB… See the full description on the dataset page: https://huggingface.co/datasets/visionscaper/agentic-llm-pretraining-1.7b-tokenized-qwen3-4k.gene-llm-agents-instruct
llm-agents-instruct v116
Auto-built (demand): 1 open request(s) and 0 recent download(s) for 'llm-agents' with no dataset newer than 14 days
Kind: synthetic
Domain: llm-agents
Records: 1000
Created: 2026-07-08T17:36:15+00:00
SHA-256: 281020e4a1db9e063ea6eaf359b69cfa40a89f13faeae521a4179cec586fc10c
Pipeline: v2.0.0
Filters: {"min_quality": 0.55, "limit": 1000, "source": null, "backend": "llama", "min_judge": 0.7}
Generated by: Qwen3-4B-Instruct-2507-Q4_K_M.gguf (backend:… See the full description on the dataset page: https://huggingface.co/datasets/Gene829/gene-llm-agents-instruct.gene-llm-agents-corpus
llm-agents-corpus v92
Auto-built (demand): 1 open request(s) and 0 recent download(s) for 'llm-agents' with no dataset newer than 14 days
Kind: scraped
Domain: llm-agents
Records: 702
Created: 2026-07-08T17:36:14+00:00
SHA-256: 74c00af747e66d1d4abf248168263fb9d5f1e424182d7adcdef160533c32dae2
Pipeline: v2.0.0
Filters: {"min_quality": 0.55, "limit": 1000, "source": null, "backend": null, "min_judge": null}
Sources
huggingface: 301
papers: 197
arxiv: 145
github:… See the full description on the dataset page: https://huggingface.co/datasets/Gene829/gene-llm-agents-corpus.agentic-llm-pretraining-1.7b
Agentic LLM Pretraining Dataset
A pretraining corpus for small language models (1-3B parameters) optimized for agentic tasks. The corpus emphasizes learning to comprehend language, reason, follow instructions, and use tools over memorizing factual knowledge — the assumption is that domain knowledge will be provided at runtime via RAG. The idea is that this could enable much smaller pretraining corpora by omitting the large volumes of text typically needed to memorize facts.… See the full description on the dataset page: https://huggingface.co/datasets/travisp83/agentic-llm-pretraining-1.7b.whissle-agent-llm-training-data
Whissle Agent LLM Training Data
Training and validation data for the Whissle Agent LoRA model.
Each sample is a (perception, response) pair where:
Perception = structured ASR output (transcript + emotion + intent + entities + MI behavior)
Response = ideal agent response with SSML prosody, tool calls, MI codes, and reasoning
Dataset Statistics
Split
Samples
Training
5,171
Validation
272
Total
5,443
By Domain
Domain
File… See the full description on the dataset page: https://huggingface.co/datasets/WhissleAI/whissle-agent-llm-training-data.