6 papers
GPO: Learning from Critical Steps to Improve LLM Reasoning
Jiahao Yu, Zelei Cheng, Xian Wu +1
Large language models (LLMs) are increasingly used in various domains, showing impressive potential on different tasks. Recently, reasoning LLMs have been proposed to improve the \…
Building Coding Agents via Entropy-Enhanced Multi-Turn Preference Optimization
Jiahao Yu, Zelei Cheng, Xian Wu +1
Software engineering presents complex, multi-step challenges for Large Language Models (LLMs), requiring reasoning over large codebases and coordinated tool use. The difficulty of…
VSA:Visual-Structural Alignment for UI-to-Code
Xian Wu, Ming Zhang, Zhiyu Fang +4
The automation of user interface development has the potential to accelerate software delivery by mitigating intensive manual implementation. Despite the advancements in Large Mult…
BlockScan: Detecting Anomalies in Blockchain Transactions
Jiahao Yu, Xian Wu, Hao Liu +2
We propose BlockScan, a customized Transformer for anomaly detection in blockchain transactions. Unlike existing methods that rely on rule-based systems or directly apply off-the-s…
Socratic RL: A Novel Framework for Efficient Knowledge Acquisition through Iterative Reflection and Viewpoint Distillation
Xiangfan Wu
Current Reinforcement Learning (RL) methodologies for Large Language Models (LLMs) often rely on simplistic, outcome-based reward signals (e.g., final answer correctness), which li…
Soft-Label Integration for Robust Toxicity Classification
Zelei Cheng, Xian Wu, Jiahao Yu +3
Toxicity classification in textual content remains a significant problem. Data with labels from a single annotator fall short of capturing the diversity of human perspectives. Ther…