research-agent
gaia2
Gaia2
Paper | Code | Project Page
Dataset Summary
Gaia2 is a benchmark dataset for evaluating AI agent capabilities in simulated environments. The dataset contains 800 scenarios that test agent performance in environments where time flows continuously and events occur dynamically.
The dataset evaluates seven core capabilities: Execution (multi-step planning and state changes), Search (information gathering and synthesis), Adaptability (dynamic response to environmental… See the full description on the dataset page: https://huggingface.co/datasets/meta-agents-research-environments/gaia2.gaia2_filesystem
GAIA2 Filesystem
This is a dataset containing files for the GAIA2 benchmark. You should not use this dataset on its own, but instead use the Meta Agents Research Environments framework to execute scenarios from that GAIA2 dataset.
Dataset Link
https://huggingface.co/datasets/meta-agents-research-environments/gaia2
Contact Details
Publishing POC: Meta AI Research Team
Affiliation: Meta Platforms, Inc.
Website:… See the full description on the dataset page: https://huggingface.co/datasets/meta-agents-research-environments/gaia2_filesystem.research-agent-rl-episodesgaia2-cli
GAIA2 CLI
Benchmark dataset for gaia2-cli, the CLI-based agent evaluation harness.
Schema
Each row has two columns:
Column
Type
Description
scenario_id
string
Unique scenario identifier (e.g. scenario_universe_21_1qgjj6)
scenario
string
Complete scenario as a JSON string
Usage
from datasets import load_dataset
import json
# Load a specific config (160 scenarios)
ds = load_dataset("meta-agents-research-environments/gaia2-cli", "adaptability"… See the full description on the dataset page: https://huggingface.co/datasets/meta-agents-research-environments/gaia2-cli.tool-reasoning-sft-RESEARCH-openresearcher-dataset-sft-deep-research-agent-data-cleaned
OpenResearcher Dataset - Cleaned & Restructured
👥 Follow the Author
Aman Priyanshu
Overview
This dataset is a cleaned and restructured version of the OpenResearcher Dataset released by the TIGER-AI-Lab. The original dataset contains 96K+ long-horizon deep research trajectories generated by GPT-OSS-120B with native browser tools. This version converts the GPT-OSS channel-based message format into a standardized multi-turn tool-use conversation… See the full description on the dataset page: https://huggingface.co/datasets/AmanPriyanshu/tool-reasoning-sft-RESEARCH-openresearcher-dataset-sft-deep-research-agent-data-cleaned.agent-trajectories-swe-bench-test-minus-verified
Agent Trajectories: SWE-bench Test \ Verified — Mixed Teachers (gpt-5.2 / gpt-5-mini)
Summary
Full multi-turn agent trajectories collected from the SWE-bench Test minus Verified split
(i.e., SWE-bench Test instances that are not part of SWE-bench Verified).
Intended for SFT of agent models on coding tasks.
Data Collection
Each trajectory was produced by a GT-aware lookahead agent that, at every turn:
Sampled a candidate response from both gpt-5.2 and… See the full description on the dataset page: https://huggingface.co/datasets/JetBrains-Research/agent-trajectories-swe-bench-test-minus-verified.