Author

Bo Wang

h-index 2 View on Semantic Scholar

We have 5 of 6 papers

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

#computer vision Preprint Oct 2026

OpenMobile-2: Building Versatile Mobile Agents with Scalable Environments and App-Native Tools

We introduce OpenMobile-2, a near-frontier mobile agent with fully open training environments and recipes. We make three key advances: (1) Diverse environments with simulated commercial apps: We build MobileGym++, featuring 35 realistic, functionally rich commercial-style apps with cross-app workflows, while preserving...

Chen-Yang Yan, Ying-Ying Zhang, Kanzhi Cheng et al. · 0 citations

#artificial intelligence Preprint Oct 2026

PEARL: Process-Experience Aware Reinforcement Learning for Multi-Turn Agents

Terminal rewards make multi-turn agents trainable without step-level annotations, but group-relative advantages provide little guidance about which intermediate decisions to adjust. Failed trajectories also contain reasonable actions, while unfavorable decision patterns can recur as training proceeds. We introduce PEAR...

Jie Yang, Mian-Qiu Huang, Yi-Wei Zhao et al. · 0 citations

#artificial intelligence Preprint Sep 2026

When Can Agents Forget Their Reasoning? ICLR for Long-Horizon Agent Context Compression

Results characterize agent reasoning as dynamic working state rather than permanent interaction history, and suggest that historical reasoning becomes more replaceable once task relevant derived state has been reliably externalized into code, files, tool outputs, or environmental feedback.

Ming-Xuan Wang, Fei Luo, Bo Wang et al. · 0 citations

#small language model Preprint Sep 2026

DRSR: Learning Set-Level Deletion Risk for Efficient Long-Horizon Agents

Direct Relational Set-Risk Pruning is introduced, which formulates agent-history compression as risk-constrained selection over deletion sets and shows that decision-conditioned relations, retained-context information, pair interactions, and abstention each contribute to reliable pruning.

Ming-Xuan Wang, Bo Wang, Fei Luo et al. · 0 citations

Preprint Aug 2026

ContextWeave: A Real-World Workflow Benchmark

ContextWeave is introduced, a longitudinal benchmark that evaluates whether recalled experience improves downstream agent performance in realistic office-work streams and motivates memory systems that optimize not only retrieval relevance but also reliable use during execution.

Bo Wang, Yu Yao, Enxi Wang et al. · 0 citations