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DRACULA dataset introduces user feedback on intermediate actions for research agents

By PulseAugur Editorial · [2 sources] ·

Researchers have introduced DRACULA, a new dataset designed to improve deep research agents by capturing user feedback on intermediate actions. The dataset, collected from 19 expert CS researchers, includes over 8,000 action preferences and 5,000 execution judgments related to synthesizing research papers. Initial findings indicate that large language models struggle to predict user-preferred actions, especially when users have unstated goals, highlighting the need for better action feedback mechanisms for long-horizon agents. AI

IMPACT Provides a new dataset for training and evaluating AI agents on complex, multi-step tasks.

RANK_REASON The cluster describes a new dataset and paper published on arXiv.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

DRACULA dataset introduces user feedback on intermediate actions for research agents

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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Nishant Balepur, Malachi Hamada, Varsha Kishore, Sergey Feldman, Amanpreet Singh, Pao Siangliulue, Joseph Chee Chang, Rachel Rudinger, Eunsol Choi, Jordan Lee Boyd-Graber, Doug Downey, Aakanksha Naik ·

    DRACULA: Hunting for the Actions Users Want Deep Research Agents to Execute

    arXiv:2604.23815v1 Announce Type: new Abstract: Scientific Deep Research (DR) agents answer user queries by synthesizing research papers into multi-section reports. User feedback can improve their utility, but existing protocols only score the final report, making it hard to stud…

  2. arXiv cs.CL TIER_1 English(EN) · Aakanksha Naik ·

    DRACULA: Hunting for the Actions Users Want Deep Research Agents to Execute

    Scientific Deep Research (DR) agents answer user queries by synthesizing research papers into multi-section reports. User feedback can improve their utility, but existing protocols only score the final report, making it hard to study and learn which intermediate actions DR agents…

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