Dimensions overall score 8.0

GitHub Code Pulse

No public code linked for this paper yet.

• PaperSearchQA introduces a search corpus of 16 million biomedical paper abstractstechnical 95%
• PaperSearchQA constructs a factoid QA dataset with 60k samples answerable from the corpustechnical 95%
• Search agents trained with RLVR in this environment outperform non-RL retrieval baselinesresult 85%
• The paper's data creation methods are scalable and easily extendable to other scientific domainsmethod 80%
• Most RLVR search agents tackle general-domain QA, limiting relevance to technical AI systems in science, engineering, and medicinelimitation 90%
• Training agents to search and reason over scientific papers tests technical question-answering capabilitiestechnical 85%
• The corpus, datasets, and benchmarks are usable with the popular Search-R1 codebase for RLVR trainingtechnical 90%
• The paper observes interesting agent behaviors like planning, reasoning, and self-verificationresult 80%

Competitive landscape

Competitor map is still being generated for this paper. Enable generation or check back soon.

Startup potential card