1 citations · 1 across the 2 of their papers we have counts for
7 papers
A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Code
Keke Lian, Bin Wang, Lei Zhang +19
The increasing adoption of large language models (LLMs) in software engineering necessitates rigorous security evaluation of their generated code. However, existing benchmarks ofte…
PeRL: Permutation-Enhanced Reinforcement Learning for Interleaved Vision-Language Reasoning
Yizhen Zhang, Yang Ding, Shuoshuo Zhang +9
Inspired by the impressive reasoning capabilities demonstrated by reinforcement learning approaches like DeepSeek-R1, recent emerging research has begun exploring the use of reinfo…
Zero-P-to-3: Zero-Shot Partial-View Images to 3D Object
Yuxuan Lin, Ruihang Chu, Zhenyu Chen +9
Generative 3D reconstruction shows strong potential in incomplete observations. While sparse-view and single-image reconstruction are well-researched, partial observation remains u…
ProReflow: Progressive Reflow with Decomposed Velocity
Lei Ke, Haohang Xu, Xuefei Ning +7
Diffusion models have achieved significant progress in both image and video generation while still suffering from huge computation costs. As an effective solution, flow matching ai…
Teaching Your Models to Understand Code via Focal Preference Alignment
Jie Wu, Haoling Li, Xin Zhang +8
Preference learning extends the performance of Code LLMs beyond traditional supervised fine-tuning by leveraging relative quality comparisons. In existing approaches, a set of n ca…
EpiCoder: Encompassing Diversity and Complexity in Code Generation
Yaoxiang Wang, Haoling Li, Xin Zhang +10
Existing methods for code generation use code snippets as seed data, restricting the complexity and diversity of the synthesized data. In this paper, we introduce a novel feature t…