9 papers
Exposing Weaknesses of Large Reasoning Models through Graph Algorithm Problems
Qifan Zhang, Jianhao Ruan, Aochuan Chen +4
Large Reasoning Models (LRMs) have advanced rapidly; however, existing benchmarks in mathematics, code, and common-sense reasoning remain limited. They lack long-context evaluation…
Mitigating the Safety Alignment Tax with Null-Space Constrained Policy Optimization
Yifan Niu, Han Xiao, Dongyi Liu +2
As Large Language Models (LLMs) are increasingly deployed in real-world applications, it is important to ensure their behaviors align with human values, societal norms, and ethical…
Incentivizing In-depth Reasoning over Long Contexts with Process Advantage Shaping
Miao Peng, Weizhou Shen, Nuo Chen +3
Reinforcement Learning with Verifiable Rewards (RLVR) has proven effective in enhancing LLMs short-context reasoning, but its performance degrades in long-context scenarios that re…
AlgBench: To What Extent Do Large Reasoning Models Understand Algorithms?
Henan Sun, Kaichi Yu, Yuyao Wang +5
Reasoning ability has become a central focus in the advancement of Large Reasoning Models (LRMs). Although notable progress has been achieved on several reasoning benchmarks such a…
Is AI mingling or bullying me? Exploring User Interactions with a Chatbot in China
Nuo Chen, Pu Yan, Jia Li +1
Since its viral emergence in early 2024, Comment Robert-a Weibo-launched social chatbot-has gained widespread attention on the Chinese Internet for its unsolicited and unpredictabl…
Revisiting LoRA through the Lens of Parameter Redundancy: Spectral Encoding Helps
Jiashun Cheng, Aochuan Chen, Nuo Chen +4
Low-Rank Adaptation (LoRA) has emerged as a prominent technique for fine-tuning large foundation models. Despite its successes, the substantial parameter redundancy, which limits t…