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cs.AI2026
AgentFold: Closed-Loop Agentic Search for Protein Folding Model Design
Mingquan Liu, Jiangyu Chen, Hanqun Cao +9
Scientific LLM agents have shown promise in literature reasoning, tool use, and experiment planning, but it remains unclear whether they can autonomously improve large, tightly cou…
cs.AI2026
Capturing LLM Capabilities via Evidence-Calibrated Query Clustering
Fangzhou Wu, Sandeep Silwal, Qiuyi Zhang
Query clustering organizes queries into groups that reflect shared latent capability demands, enabling capability-aware LLM evaluation. Existing clustering methods, which primarily…
cs.AI2026
Latent Action Reparameterization for Efficient Agent Inference
Wenhao Huang, Qingwen Zeng, Qiyue Chen +11
Large language model (LLM) agents often rely on long sequences of low-level textual actions, resulting in large effective decision horizons and high inference cost. While prior wor…