Hugging Face Trending Papers
BioStudyBench: Evaluating Agents on Post-Cutoff Biomedical Studies
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arXiv AI
Oct 7
BioStudyBench: Evaluating Agents on Post-Cutoff Biomedical Studies
BioStudyBench is a new benchmark that tests AI agents on 25 long‑horizon analysis tasks derived from biomedical studies published between July and September 2026, after the models’ knowledge cutoffs. Each task gives the agent a neutral research question but no data files, requiring it to locate and download relevant public data, search literature using tools limited to pre‑cutoff records, and perform data analysis to report findings. The benchmark shows that providing data and tools improves model performance by an average of 47 percentage points, with closed‑weight models outperforming open‑weight ones (best open‑weight 81.3% vs. best closed‑weight 94.7%).
arXiv AI
Jun 24
BioMedArena: An Open-source Toolkit for Building and Evaluating Biomedical Deep Research Agents
arXiv:2605. 06177v2 Announce Type: replace Abstract: Reproducing and comparing deep research agents today is hard: the same backbone evaluated on the same benchmark can report different accuracies across papers because the harness and tool registry differ, and integrating a new model into a comparable evaluation surface costs weeks of model-specific engineering.
arXiv AI
Jun 30
DEEPMED Search: An Open-Source Agentic Platform for Medical Deep Research with Introspective Verification
arXiv:2606. 29746v1 Announce Type: new Abstract: Navigating the deluge of heterogeneous medical data, from academic literature (PubMed) to clinical guidelines (Web) and private knowledge bases, remains a critical bottleneck for evidence-based medicine.
Hugging Face Trending Papers
Jun 29
DEEPMED Search: An Open-Source Agentic Platform for Medical Deep Research with Introspective Verification
Navigating the deluge of heterogeneous medical data, from academic literature (PubMed) to clinical guidelines (Web) and private knowledge bases, remains a critical bottleneck for evidence-based medicine. While commercial black-box tools lack transparency, standard open-source RAG implementations frequently suffer from reasoning drift when handling complex, long-tail queries.
arXiv AI
Aug 7
CT Open: An Open-Access, Uncontaminated, Live Platform for the Open Challenge of Clinical Trial Outcome Prediction
arXiv:2604. 16742v2 Announce Type: replace Abstract: Scientists have long sought to accurately predict outcomes of real-world events before they happen.
arXiv Machine Learning
Jul 31
EMBL AI Librarian: Life-Sciences Knowledge Layer for AI Agents
arXiv:2607. 28229v1 Announce Type: cross Abstract: The web is increasingly accessed by AI agents rather than humans.