7 papers
Deconstructing Positional Information: From Attention Logits to Training Biases
Zihan Gu, Ruoyu Chen, Han Zhang +2
Positional encodings enable Transformers to incorporate sequential information, yet their theoretical understanding remains limited to two properties: distance attenuation and tran…
PromptRL: Prompt Matters in RL for Flow-Based Image Generation
Fu-Yun Wang, Han Zhang, Michael Gharbi +2
Flow matching models (FMs) have revolutionized text-to-image (T2I) generation, with reinforcement learning (RL) serving as a critical post-training strategy for alignment with rewa…
Nemotron-Flash: Towards Latency-Optimal Hybrid Small Language Models
Yonggan Fu, Xin Dong, Shizhe Diao +12
Efficient deployment of small language models (SLMs) is essential for numerous real-world applications with stringent latency constraints. While previous work on SLM design has pri…
UniRL-Zero: Reinforcement Learning on Unified Models with Joint Language Model and Diffusion Model Experts
Fu-Yun Wang, Han Zhang, Michael Gharbi +2
We present UniRL-Zero, a unified reinforcement learning (RL) framework that boosts, multimodal language model understanding and reasoning, diffusion model multimedia generation, an…
BenCao: An Instruction-Tuned Large Language Model for Traditional Chinese Medicine
Jiacheng Xie, Yang Yu, Yibo Chen +7
Traditional Chinese Medicine (TCM), with a history spanning over two millennia, plays a role in global healthcare. However, applying large language models (LLMs) to TCM remains cha…
CHURRO: Making History Readable with an Open-Weight Large Vision-Language Model for High-Accuracy, Low-Cost Historical Text Recognition
Sina J. Semnani, Han Zhang, Xinyan He +2
Accurate text recognition for historical documents can greatly advance the study and preservation of cultural heritage. Existing vision-language models (VLMs), however, are designe…