3 citations · 6 across the 11 of their papers we have counts for
12 papers
Geometric Regularization for Long-Tailed Semi-Supervised Learning via Gaussian Feature Bridges
Hongyang He, Xinyuan Song, Yan Zhong +4
Real-world semi-supervised learning (SSL) often encounters significant challenges with long-tailed label distributions and noisy pseudo-labels, which hinder generalization and ampl…
CML-Bench: A Framework for Evaluating and Enhancing LLM-Powered Movie Scripts Generation
Mingzhe Zheng, Dingjie Song, Guanyu Zhou +7
Large Language Models (LLMs) have demonstrated remarkable proficiency in generating highly structured texts. However, while exhibiting a high degree of structural organization, mov…
TRiCo: Triadic Game-Theoretic Co-Training for Robust Semi-Supervised Learning
Hongyang He, Xinyuan Song, Yangfan He +5
We introduce TRiCo, a novel triadic game-theoretic co-training framework that rethinks the structure of semi-supervised learning by incorporating a teacher, two students, and an ad…
Low-Cost Test-Time Adaptation for Robust Video Editing
Jianhui Wang, Yinda Chen, Yangfan He +6
Video editing is a critical component of content creation that transforms raw footage into coherent works aligned with specific visual and narrative objectives. Existing approaches…
Optimizing Multi-Round Enhanced Training in Diffusion Models for Improved Preference Understanding
Kun Li, Jianhui Wang, Yangfan He +10
Generative AI has significantly changed industries by enabling text-driven image generation, yet challenges remain in achieving high-resolution outputs that align with fine-grained…
Efficient Temporal Consistency in Diffusion-Based Video Editing with Adaptor Modules: A Theoretical Framework
Xinyuan Song, Yangfan He, Sida Li +10
Adapter-based methods are commonly used to enhance model performance with minimal additional complexity, especially in video editing tasks that require frame-to-frame consistency.…
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…
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…
Free-Mask: A Novel Paradigm of Integration Between the Segmentation Diffusion Model and Image Editing
Bo Gao, Jianhui Wang, Xinyuan Song +3
Current semantic segmentation models typically require a substantial amount of manually annotated data, a process that is both time-consuming and resource-intensive. Alternatively,…
Enhancing Commentary Strategies for Imperfect Information Card Games: A Study of Large Language Models in Guandan Commentary
Meiling Tao, Xuechen Liang, Xinyuan Song +4
Recent advancements in large language models (LLMs) have unlocked the potential for generating high-quality game commentary. However, producing insightful and engaging commentary f…