10 citations · 11 across the 5 of their papers we have counts for
5 papers
Is Next-Chunk Reasoning RL Really Better than SFT? Revisiting Training Strategies under no-CoT Data
Yinhao Tang, Youqing Fang, Yanan Sun +8
Recent work proposes next-chunk reasoning RL for leveraging no-CoT data---corpora such as worked solutions and textbook derivations that contain reasoning-rich content but lack exp…
MindCopilot: Towards Formalizing and Evaluating Granular Human-LLM Co-Writing
Youqing Fang, Yinhao Tang, Yanan Sun +8
Recent writing assistants are increasingly shifting from passive, prompt-driven interaction to proactive, suggestion-based completion, which integrates localized continuations into…
Unveiling the Misuse Potential of Base Large Language Models via In-Context Learning
Xiao Wang, Tianze Chen, Xianjun Yang +3
The open-sourcing of large language models (LLMs) accelerates application development, innovation, and scientific progress. This includes both base models, which are pre-trained on…
Navigating the OverKill in Large Language Models
Chenyu Shi, Xiao Wang, Qiming Ge +7
Large language models are meticulously aligned to be both helpful and harmless. However, recent research points to a potential overkill which means models may refuse to answer beni…
Shadow Alignment: The Ease of Subverting Safely-Aligned Language Models
Xianjun Yang, Xiao Wang, Qi Zhang +4
Warning: This paper contains examples of harmful language, and reader discretion is recommended. The increasing open release of powerful large language models (LLMs) has facilitate…