11 papers
Twin Co-Adaptive Dialogue for Progressive Image Generation
Jianhui Wang, Yangfan He, Yan Zhong +12
Modern text-to-image generation systems have enabled the creation of remarkably realistic and high-quality visuals, yet they often falter when handling the inherent ambiguities in…
DebFlow: Automating Agent Creation via Agent Debate
Jinwei Su, Yinghui Xia, Yiqun Duan +4
Large language models (LLMs) have demonstrated strong potential and impressive performance in automating the generation and optimization of workflows. However, existing approaches…
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 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…
TDRI: Two-Phase Dialogue Refinement and Co-Adaptation for Interactive Image Generation
Yuheng Feng, Jianhui Wang, Kun Li +5
Although text-to-image generation technologies have made significant advancements, they still face challenges when dealing with ambiguous prompts and aligning outputs with user int…
A Cascading Cooperative Multi-agent Framework for On-ramp Merging Control Integrating Large Language Models
Miao Zhang, Zhenlong Fang, Tianyi Wang +4
Traditional Reinforcement Learning (RL) suffers from replicating human-like behaviors, generalizing effectively in multi-agent scenarios, and overcoming inherent interpretability i…