1 citations · 1 across the 2 of their papers we have counts for
4 papers
Reasoning Can Be Restored by Correcting a Few Decision Tokens
Changshuo Shen, Leheng Sheng, Yuxin Chen +2
Large reasoning models (LRMs) substantially outperform their base LLM counterparts on challenging reasoning benchmarks, yet it remains poorly understood where base models go wrong…
On Reasoning Strength Planning in Large Reasoning Models
Leheng Sheng, An Zhang, Zijian Wu +5
Recent studies empirically reveal that large reasoning models (LRMs) can automatically allocate more reasoning strengths (i.e., the number of reasoning tokens) for harder problems,…
AlphaSteer: Learning Refusal Steering with Principled Null-Space Constraint
Leheng Sheng, Changshuo Shen, Weixiang Zhao +6
As LLMs are increasingly deployed in real-world applications, ensuring their ability to refuse malicious prompts, especially jailbreak attacks, is essential for safe and reliable u…
Surfer100: Generating Surveys From Web Resources, Wikipedia-style
Irene Li, Alexander Fabbri, Rina Kawamura +7
Fast-developing fields such as Artificial Intelligence (AI) often outpace the efforts of encyclopedic sources such as Wikipedia, which either do not completely cover recently-intro…