6 papers
DTP: A Simple yet Effective Distracting Token Pruning Framework for Vision-Language Action Models
Chenyang Li, Jieyuan Liu, Bin Li +5
Vision-Language Action (VLA) models have shown remarkable progress in robotic manipulation by leveraging the powerful perception abilities of Vision-Language Models (VLMs) to under…
CME-CAD: Heterogeneous Collaborative Multi-Expert Reinforcement Learning for CAD Code Generation
Ke Niu, Haiyang Yu, Zhuofan Chen +7
Computer-Aided Design (CAD) is essential in industrial design, but the complexity of traditional CAD modeling and workflows presents significant challenges for automating the gener…
SCORE: Story Coherence and Retrieval Enhancement for AI Narratives
Qiang Yi, Yangfan He, Jianhui Wang +18
Large Language Models (LLMs) can generate creative and engaging narratives from user-specified input, but maintaining coherence and emotional depth throughout these AI-generated st…
Enhancing Intent Understanding for Ambiguous prompt: A Human-Machine Co-Adaption Strategy
Yangfan He, Jianhui Wang, Yijin Wang +18
Current image generation systems produce high-quality images but struggle with ambiguous user prompts, making interpretation of actual user intentions difficult. Many users must mo…
Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey
Junqiao Wang, Zeng Zhang, Yangfan He +18
With the rapid evolution of large language models (LLM), reinforcement learning (RL) has emerged as a pivotal technique for code generation and optimization in various domains. Thi…
Attentive Eraser: Unleashing Diffusion Model's Object Removal Potential via Self-Attention Redirection Guidance
Wenhao Sun, Benlei Cui, Xue-Mei Dong +1
Recently, diffusion models have emerged as promising newcomers in the field of generative models, shining brightly in image generation. However, when employed for object removal ta…