6 papers
Accelerating IC Thermal Simulation Data Generation via Block Krylov and Operator Action
Hong Wang, Wenkai Yang, Jie Wang +6
Recent advances in data-driven approaches, such as neural operators (NOs), have shown substantial efficacy in reducing the solution time for integrated circuit (IC) thermal simulat…
GAPO: Robust Advantage Estimation for Real-World Code LLMs
Jianqing Zhang, Zhezheng Hao, Wei Xia +7
Reinforcement learning (RL) is widely used for post-training large language models (LLMs) in code editing, where group-relative methods, such as GRPO, are popular due to their crit…
AP2O-Coder: Adaptively Progressive Preference Optimization for Reducing Compilation and Runtime Errors in LLM-Generated Code
Jianqing Zhang, Wei Xia, Hande Dong +2
LLMs' code generation capabilities have yielded substantial improvements in the effectiveness of programming tasks. However, LLM-generated code still suffers from compilation and r…
Unleashing the True Potential of LLMs: A Feedback-Triggered Self-Correction with Long-Term Multipath Decoding
Jipeng Li, Zeyu Gao, Yubin Qi +3
Large Language Models (LLMs) have achieved remarkable performance across diverse tasks, yet their susceptibility to generating incorrect content during inference remains a critical…
UniSVG: A Unified Dataset for Vector Graphic Understanding and Generation with Multimodal Large Language Models
Jinke Li, Jiarui Yu, Chenxing Wei +5
Unlike bitmap images, scalable vector graphics (SVG) maintain quality when scaled, frequently employed in computer vision and artistic design in the representation of SVG code. In…
ReDit: Reward Dithering for Improved LLM Policy Optimization
Chenxing Wei, Jiarui Yu, Ying Tiffany He +3
DeepSeek-R1 has successfully enhanced Large Language Model (LLM) reasoning capabilities through its rule-based reward system. While it's a ''perfect'' reward system that effectivel…