9 papers
Logit Arithmetic Elicits Long Reasoning Capabilities Without Training
Yunxiang Zhang, Muhammad Khalifa, Lechen Zhang +5
Large reasoning models exhibit long chain-of-thought reasoning with complex strategies such as backtracking and self-verification. Yet, these capabilities typically require resourc…
Context Over Content: Exposing Evaluation Faking in Automated Judges
Manan Gupta, Inderjeet Nair, Lu Wang +1
The paradigm has become the operational backbone of automated AI evaluation pipelines, yet rests on an unverified assumption: that judges evaluate text st…
Beyond State Consistency: Behavior Consistency in Text-Based World Models
Youling Huang, Guanqiao Chen, Junchi Yao +8
World models have been emerging as critical components for assessing the consequences of actions generated by interactive agents in online planning and offline evaluation. In text-…
DUET: Joint Exploration of User Item Profiles in Recommendation System
Yue Chen, Yifei Sun, Lu Wang +17
Traditional recommendation systems represent users and items as dense vectors and learn to align them in a shared latent space for relevance estimation. Recent LLM-based recommende…
Think Through Uncertainty: Improving Long-Form Generation Factuality via Reasoning Calibration
Xin Liu, Lu Wang
Large language models (LLMs) often hallucinate in long-form generation. Existing approaches mainly improve factuality through post-hoc revision or reinforcement learning (RL) with…
Answer Convergence as a Signal for Early Stopping in Reasoning
Xin Liu, Lu Wang
Chain-of-thought (CoT) prompting enhances reasoning in large language models (LLMs) but often leads to verbose and redundant outputs, thus increasing inference cost. We hypothesize…