3 papers
cs.AI2026
DISCERN: Can AI Agents Work Like Scientists and Guide Discovery?
Nan Huang, Mario Tapia-Pacheco, Kun Zhou +4
Reliable automated research requires agents to vet data, verify analyses, and generate hypotheses grounded in trustworthy evidence, potentially reducing routine scientific workload…
cs.LG2026
EvoLen: Evolution-Guided Tokenization for DNA Language Model
Nan Huang, Xiaoxiao Zhou, Junxia Cui +4
Tokens serve as the basic units of representation in DNA language models (DNALMs), yet their design remains underexplored. Unlike natural language, DNA lacks inherent token boundar…
cs.CL2024
Entangled Relations: Leveraging NLI and Meta-analysis to Enhance Biomedical Relation Extraction
William Hogan, Jingbo Shang
Recent research efforts have explored the potential of leveraging natural language inference (NLI) techniques to enhance relation extraction (RE). In this vein, we introduce MetaEn…