5 citations · 12 across the 6 of their papers we have counts for
7 papers
WeightBridge: An Efficient Weight Transfer Library for Reinforcement Learning
Xuanlin Jiang, Samuel Hsia, Michael Kuchnik +3
Weight transfer - the propagation of updated parameters from trainers to rollout generators - is becoming an important performance bottleneck in reinforcement learning (RL) systems…
T2MBench: A Benchmark for Out-of-Distribution Text-to-Motion Generation
Bin Yang, Rong Ou, Weisheng Xu +7
Most existing evaluations of text-to-motion generation focus on in-distribution textual inputs and a limited set of evaluation criteria, which restricts their ability to systematic…
Scaling Beyond Context: A Survey of Multimodal Retrieval-Augmented Generation for Document Understanding
Sensen Gao, Shanshan Zhao, Xu Jiang +7
Document understanding is critical for applications from financial analysis to scientific discovery. Current approaches, whether OCR-based pipelines feeding Large Language Models (…
UI-TARS: Pioneering Automated GUI Interaction with Native Agents
Yujia Qin, Yining Ye, Junjie Fang +32
This paper introduces UI-TARS, a native GUI agent model that solely perceives the screenshots as input and performs human-like interactions (e.g., keyboard and mouse operations). U…
NEO: Saving GPU Memory Crisis with CPU Offloading for Online LLM Inference
Xuanlin Jiang, Yang Zhou, Shiyi Cao +2
Online LLM inference powers many exciting applications such as intelligent chatbots and autonomous agents. Modern LLM inference engines widely rely on request batching to improve i…
Towards Implicit Bias Detection and Mitigation in Multi-Agent LLM Interactions
Angana Borah, Rada Mihalcea
As Large Language Models (LLMs) continue to evolve, they are increasingly being employed in numerous studies to simulate societies and execute diverse social tasks. However, LLMs a…
RAGCache: Efficient Knowledge Caching for Retrieval-Augmented Generation
Chao Jin, Zili Zhang, Xuanlin Jiang +4
Retrieval-Augmented Generation (RAG) has shown significant improvements in various natural language processing tasks by integrating the strengths of large language models (LLMs) an…