1 citations · 3 across the 7 of their papers we have counts for
8 papers
Gains and Collapse in On-Policy Distillation:A Reinforcement Learning Perspective
Han Cui, Jianhao Yan, Yun Luo +3
On-policy distillation (OPD) has become an important approach to language model post-training. However, despite its performance gains, OPD can also collapse into excessively long a…
Minimizing Mismatch Risk: A Prototype-Based Routing Framework for Zero-shot LLM-generated Text Detection
Ke Sun, Guangsheng Bao, Han Cui +1
Zero-shot methods detect LLM-generated text by computing statistical signatures using a surrogate model. Existing approaches typically employ a fixed surrogate for all inputs regar…
When AI Settles Down: Late-Stage Stability as a Signature of AI-Generated Text Detection
Ke Sun, Guangsheng Bao, Han Cui +1
Zero-shot detection methods for AI-generated text typically aggregate token-level statistics across entire sequences, overlooking the temporal dynamics inherent to autoregressive g…
Scaling Reinforcement Learning for Content Moderation with Large Language Models
Hamed Firooz, Rui Liu, Yuchen Lu +15
Content moderation at scale remains one of the most pressing challenges in today's digital ecosystem, where billions of user- and AI-generated artifacts must be continuously evalua…
Deep Literature Survey Automation with an Iterative Workflow
Hongbo Zhang, Han Cui, Yidong Wang +6
Automatic literature survey generation has attracted increasing attention, yet most existing systems follow a one-shot paradigm, where a large set of papers is retrieved at once an…
Direct Value Optimization: Improving Chain-of-Thought Reasoning in LLMs with Refined Values
Hongbo Zhang, Han Cui, Guangsheng Bao +3
We introduce Direct Value Optimization (DVO), an innovative reinforcement learning framework for enhancing large language models in complex reasoning tasks. Unlike traditional meth…
An Empirical Study of False Negatives and Positives of Static Code Analyzers From the Perspective of Historical Issues
Han Cui, Menglei Xie, Ting Su +2
Static code analyzers are widely used to help find program flaws. However, in practice the effectiveness and usability of such analyzers is affected by the problems of false negati…
Exploring Hybrid Question Answering via Program-based Prompting
Qi Shi, Han Cui, Haofeng Wang +3
Question answering over heterogeneous data requires reasoning over diverse sources of data, which is challenging due to the large scale of information and organic coupling of heter…