works on

From the 2 of 7 linked papers with an AI index.

collaborators

7 papers

cs.LG2026

TideRL: Boosting Agentic RL Goodput with Readiness-Aware Scheduling

Yanyu Ren, Xizheng Wang, Xiao Liu +8

Reinforcement learning (RL) for large language models is moving toward multi-turn agentic workloads, where rollout tasks repeatedly pause for external environments, resume with gro…

cs.AI2026

An Empirical Study of Coordination Mode as the First-Class Citizen in From-Scratch Multi-Agent Coding

Yanyu Ren, Yunfeng Bai, Xizheng Wang +2

The paper presents MSEval, a benchmark that evaluates how multi‑agent coding systems build real‑world software, measuring functional success, latency, and token cost while varying…

cs.AI2026

SCALECUA: Scaling Computer Use Agents with Verifiable Task Synthesis and Efficient Online RL

Bowen Lv, Xiao Liu, Yanyu Ren +7

The paper introduces ScaleCUA, a framework that generates verifiable tasks and improves online reinforcement learning efficiency for computer use agents, achieving state-of-the-art…

cs.DC2025

Communication-Efficient Serving for Video Diffusion Models with Latent Parallelism

Zhiyuan Wu, Shuai Wang, Li Chen +5

Video diffusion models (VDMs) perform attention computation over the 3D spatio-temporal domain. Compared to large language models (LLMs) processing 1D sequences, their memory consu…

cs.AI2025

DMA: Online RAG Alignment with Human Feedback

Yu Bai, Yukai Miao, Dawei Wang +9

Retrieval-augmented generation (RAG) systems often rely on static retrieval, limiting adaptation to evolving intent and content drift. We introduce Dynamic Memory Alignment (DMA),…

cs.AI2025

ComputerRL: Scaling End-to-End Online Reinforcement Learning for Computer Use Agents

Hanyu Lai, Xiao Liu, Yanxiao Zhao +7

We introduce ComputerRL, a framework for autonomous desktop intelligence that enables agents to operate complex digital workspaces skillfully. ComputerRL features the API-GUI parad…