🔥 QUEST: Training Frontier Deep Research Agents with Fully Synthetic Tasks

💡 The paper introduces QUEST, a family of open deep research agents that can perform well across diverse long horizon search tasks. The problem addressed is that existing open agents often generalize poorly across different task types, while frontier systems remain proprietary. To solve this, the authors propose a training recipe that combines mid training, supervised fine tuning, and reinforcement learning. A key component of this recipe is a curated data synthesis pipeline that applies to different task types and enables synthesizing training data with verifiable rewards without human annotation. The pipeline uses unified rubric trees to generate tasks. The authors also incorporate a built in context management mechanism that enables effective long horizon reasoning and knowledge synthesis. The results show that QUEST approaches or surpasses frontier closed source agents across eight deep research benchmarks using only 8K synthesized tasks. The models, data, and training scripts are released, making it possible for others to use and build upon the work. The contributions of the paper are the proposed training recipe, the data synthesis pipeline, and the release of the QUEST models, which provide a general purpose deep research agent that can handle a wide range of tasks, including fact seeking, citation grounding, and report synthesis.

📅 Published on May 22

🔗 Links:
• GitHub: https://github.com/huggingface
• arXiv: https://arxiv.org/abs/2605.24218
• PDF: https://arxiv.org/pdf/2605.24218
• Project Page: https://osu-nlp-group.github.io/QUEST/

🤖 Models citing this paper:
• https://huggingface.co/osunlp/QUEST-35B-RL
• https://huggingface.co/osunlp/QUEST-35B-MT-Plus-SFT
• https://huggingface.co/osunlp/QUEST-9B

📊 Datasets citing this paper:
• https://huggingface.co/datasets/osunlp/QUEST-RL-Data
• https://huggingface.co/datasets/osunlp/QUEST-SFT-Data-Objective
• https://huggingface.co/datasets/osunlp/QUEST-SFT-Data-Open-ended

🚀 Spaces citing this paper:
• https://huggingface.co/spaces/osunlp/QUEST

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📢 By: https://xn--r1a.website/PaperNexus

#DeepResearchAgents #LongHorizonSearchTasks #SyntheticTaskGeneration #ReinforcementLearningMethods #OpenAgentArchitectures