Author

Hanchen Zhang

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Jul 2026

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

This work introduces ScaleCUA, a unified framework that scales online RL for CUAs via verifiable task synthesis and efficient training, and designs VeriGen, an end-to-end framework for generating verifiable RL tasks through iterative docker interactions and a multi-agent feedback loop.

Bowen Lv, Xiao Liu, Yanyu Ren et al. · arXiv.org · 4 citations · ⚡1

Conference Open access 2026

KARL: Reinforcement Learning for LLM Agents on Multi-Turn Knowledge-Intensive Agentic Tasks

This work introduces KARL (Knowledge-Augmented Reinforcement Learning), a framework that enables LLM agents to dynamically explore structured knowledge sources through multi-turn interactions, and empowers agents to proactively decide when and what knowledge to acquire during task execution.

Xueqiao Sun, Xiao Liu, Bowen Lv et al. · Annual Meeting of the Associ... · 0 citations

Preprint Aug 2026

TideRL: Boosting Agentic RL Goodput with Readiness-Aware Scheduling

TideRL is presented, a readiness-aware elastic RL system with Continuous Task Batching, Resource-Aware Ref-Actor Pipelining, and Elastic Resource Scaling that improves RL training goodput and reduces per-step training time across text-only and multi-modal agentic workloads.

Yanyu Ren, Xizheng Wang, Xiao Liu et al. · 0 citations