3 papers
cs.AI2026
Self-Awareness before Action: Mitigating Logical Inertia via Proactive Cognitive Awareness
Fulong Fan, Peilin Liu, Fengzhe Liu +2
Large language models perform well on many reasoning tasks, yet they often lack awareness of whether their current knowledge or reasoning state is complete. In non-interactive puzz…
cs.CL2026
Advances in LLM Reasoning Enable Flexibility in Clinical Problem-Solving
Kie Shidara, Preethi Prem, Jonathan Kim +4
Large Language Models (LLMs) have achieved high accuracy on medical question-answer (QA) benchmarks, yet their capacity for flexible clinical reasoning has been debated. Here, we a…
cs.CL2025
Limitations of Large Language Models in Clinical Problem-Solving Arising from Inflexible Reasoning
Jonathan Kim, Anna Podlasek, Kie Shidara +3
Large Language Models (LLMs) have attained human-level accuracy on medical question-answer (QA) benchmarks. However, their limitations in navigating open-ended clinical scenarios h…