5 citations · 8 across the 4 of their papers we have counts for
5 papers
RLAX: Large-Scale, Distributed Reinforcement Learning for Large Language Models on TPUs
Runlong Zhou, Lefan Zhang, Shang-Chen Wu +29
Reinforcement learning (RL) has emerged as the de-facto paradigm for improving the reasoning capabilities of large language models (LLMs). We have developed RLAX, a scalable RL fra…
DiT-Air: Revisiting the Efficiency of Diffusion Model Architecture Design in Text to Image Generation
Chen Chen, Rui Qian, Wenze Hu +8
In this work, we empirically study Diffusion Transformers (DiTs) for text-to-image generation, focusing on architectural choices, text-conditioning strategies, and training protoco…
STIV: Scalable Text and Image Conditioned Video Generation
Zongyu Lin, Wei Liu, Chen Chen +13
The field of video generation has made remarkable advancements, yet there remains a pressing need for a clear, systematic recipe that can guide the development of robust and scalab…
Multimodal Gen-AI for Fundamental Investment Research
Lezhi Li, Ting-Yu Chang, Hai Wang
This report outlines a transformative initiative in the financial investment industry, where the conventional decision-making process, laden with labor-intensive tasks such as sift…
Mini-Giants: "Small" Language Models and Open Source Win-Win
Zhengping Zhou, Lezhi Li, Xinxi Chen +1
ChatGPT is phenomenal. However, it is prohibitively expensive to train and refine such giant models. Fortunately, small language models are flourishing and becoming more and more c…