7 citations · 8 across the 9 of their papers we have counts for
9 papers
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…
An Empirical Study of Coordination Mode as the First-Class Citizen in From-Scratch Multi-Agent Coding
Yanyu Ren, Yunfeng Bai, Xizheng Wang +2
Multi-agent vibe coding promises to accelerate software development, yet existing benchmarks rely on synthetic environments that ignore practical time and monetary costs, conflate…
SCALECUA: Scaling Computer Use Agents with Verifiable Task Synthesis and Efficient Online RL
Bowen Lv, Xiao Liu, Yanyu Ren +7
Computer use agents (CUAs) are emerging as a powerful interface for automating complex digital workflows through visual perception and GUI execution. Online reinforcement learning…
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…
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),…
DeepFaith: A Domain-Free and Model-Agnostic Unified Framework for Highly Faithful Explanations
Yuhan Guo, Lizhong Ding, Shihan Jia +6
Explainable AI (XAI) builds trust in complex systems through model attribution methods that reveal the decision rationale. However, due to the absence of a unified optimal explanat…
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…
Pistis-RAG: Enhancing Retrieval-Augmented Generation with Human Feedback
Yu Bai, Yukai Miao, Li Chen +6
RAG systems face limitations when semantic relevance alone does not guarantee improved generation quality. This issue becomes particularly evident due to the sensitivity of large l…
An Empirical Study of NetOps Capability of Pre-Trained Large Language Models
Yukai Miao, Yu Bai, Li Chen +10
Nowadays, the versatile capabilities of Pre-trained Large Language Models (LLMs) have attracted much attention from the industry. However, some vertical domains are more interested…