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cs.AI2026
Precedent-Informed Reasoning: Mitigating Overthinking in Large Reasoning Models via Test-Time Precedent Learning
Qianyue Wang, Jinwu Hu, Huanxiang Lin +5
Reasoning in Large Language Models (LLMs) often suffers from inefficient long chain-of-thought traces with redundant self-exploration and validation, which inflate computational co…
cs.AI2026
Beyond Fast and Slow: Cognitive-Inspired Elastic Reasoning for Large Language Models
Jinwu Hu, Dongjin Yang, Langyu Bian +6
Large language models (LLMs) have demonstrated impressive performance across various language tasks. However, existing LLM reasoning strategies mainly rely on the LLM itself with f…
cs.AI2026
Beyond Model Scaling: Test-Time Intervention for Efficient Deep Reasoning
Qianyue Wang, Jinwu Hu, Yufeng Wang +5
Large Reasoning Models (LRMs) excel at multi-step reasoning but often suffer from inefficient reasoning processes like overthinking and overshoot, where excessive or misdirected re…