datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
deepsearchqa-react
AggAgent ReAct Rollouts - DeepSearchQA
Dataset Description
AggAgent is an agentic aggregation framework that scales long-horizon agents at test time by sampling multiple parallel rollouts from a base agent and then aggregating their evidence and solutions. This dataset card releases the ReAct base rollouts that AggAgent consumes, i.e. single-agent trajectories produced before any aggregation step.
Each rollout was generated by running a ReAct-style… See the full description on the dataset page: https://huggingface.co/datasets/yoonsanglee/deepsearchqa-react.ARPO-RL-DeepSearch-1K
ARPO Dataset: Agentic Reinforced Policy Optimization
This repository contains the datasets used in the paper Agentic Reinforced Policy Optimization.
Paper Abstract: Large-scale reinforcement learning with verifiable rewards (RLVR) has demonstrated its effectiveness in harnessing the potential of large language models (LLMs) for single-turn reasoning tasks. In realistic reasoning scenarios, LLMs can often utilize external tools to assist in task-solving processes. To bridge this gap… See the full description on the dataset page: https://huggingface.co/datasets/dongguanting/ARPO-RL-DeepSearch-1K.CS-DeepSearchQA
CS-DeepSearch (CS-DRAFT) 数据集
数据集描述
CS-DeepSearch 是一个专门为训练和评估“专家级计算机科学深层研究智能体”而设计的 QA 数据集。
数据集简介
该数据集借鉴了 MedResearcher-R1 的 KISA（知识启发式轨迹合成）框架。针对计算机科学领域，从 10,176 篇 Arxiv 摘要中挖掘出极长尾的“稀有实体”，并构建了需要复杂多跳推理链的 QA 对。
数据集支持的任务
Train: 包含 261 条深度研究 QA，可用于 SFT / RL 后训练。
Test：包含 50 条深度研究 QA，用于评估智能体的端到端研究成功率。
数据集的格式和结构
数据样本范例：
quesiton
answer
seed_entity… See the full description on the dataset page: https://huggingface.co/datasets/Leonnel1220/CS-DeepSearchQA.