collaborators

12 papers

cs.CV2026

Scaling Multi-Reference Image Generation with Dynamic Reward Optimization

Wenwang Huang, Yusen Fu, Junjie Wang +6

While personalized image generation has achieved remarkable progress, multi-reference image generation (MRIG) remains a challenging task. Most existing benchmarks fail to adequatel…

cs.AI2026

DyCon: Dynamic Reasoning Control via Evolving Difficulty Modeling

Tengyao Tu, Yulin Li, Hui-Ling Zhen +6

Recent advances in Large Reasoning Models (LRMs) demonstrate remarkable performance improvements by iteratively reflecting, exploring, and executing complex tasks, yet suffer from…

cs.CL2026

Dynamic-dLLM: Dynamic Cache-Budget and Adaptive Parallel Decoding for Training-Free Acceleration of Diffusion LLM

Tianyi Wu, Xiaoxi Sun, Yanhua Jiao +5

Diffusion Large Language Models (dLLMs) offer a promising alternative to autoregressive models, excelling in text generation tasks due to their bidirectional attention mechanisms.…

cs.AI2026

DC-Leap: Training-Free Acceleration of dLLMs via Draft-Guided Contiguous Leaping Decoding

Yanhua Jiao, Tianyi Wu, Xiaoxi Sun +6

While parallel decoding is central to the efficiency of Diffusion Large Language Models (dLLMs), current strategies are often hindered by overly conservative confidence thresholds.…

cs.CV2026

Benchmarking and Evolving Reason-Reflect-Rectify for Reflective Visual Generation

Junjie Wang, Xinghua Lou, Jason Li +8

Text-to-Image (T2I) models and Unified Multimodal Models (UMMs) have achieved remarkable progress in visual generation. However, their reliance on a single-pass generation paradigm…

cs.CV2026

AgentSteerTTS: A Multi-Agent Closed-Loop Framework for Composite-Instruction Text-to-Speech

Bin Kang, Shaoguo Wen, Yang Fan +6

While existing text-to-speech (TTS) models exhibit high expressiveness, fine-grained control over composite instructions remains challenging due to the structural mismatch between…