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Rui Xie

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#artificial intelligence Preprint Sep 2026

MatToolBench: Benchmarking Multimodal Agents in Real-World Materials Science Workflows

The experiments show that strong performance on general benchmarks does not transfer to professional scientific workflows, and that this gap is not a visual-grounding problem alone: failures arise from domain-specific operational knowledge, sparse pretraining coverage of scientific software, weak cross-tool artifact ha...

Mei-Feng Wu, Rui Xie, Run-Yu Zhang et al. · 0 citations

RecreationWorld: Scalable and Verifiable Environments for Hybrid Computer-Use Agents

This work introduces RecreationWorld, a five-platform framework built around recreation: given a running reference, an agent must discover its behavior and build a faithful implementation with no prescribed workflow, and introduces RecreationBench, comprising 250 diverse tasks across domains and platforms.

Shuai Bai, Jia-Yong Deng, Si-Cheng Fan et al. · 1 citation
#machine learning Review Sep 2026

Complex Problem Solving in Large Language Models: A Statistical Control Survey and Diagnostic Framework

This framework organizes existing methods around five components: explicit state representation, transition structuring, validation and constraint enforcement, search and rollback, and uncertainty management, and yields a diagnostic hypothesis: interventions should be most effective when they target the error or uncert...

Jia-Zhang Cai, Tao Wang, Rui-Dong Zhang et al. · 0 citations
#artificial intelligence Open access Sep 2026

AttnCompress: Dynamic Attention-Guided Trajectory Compression for Software Engineering Agents

AttnCompress bridges the gap between semantic integrity and dynamic adaptability through three key mechanisms: structure-aware segmentation via perplexity (PPL) spikes to preserve the syntactic structure of code and logs, and relevance estimation using proxy attention weights to quantify the precise relevance of histor...

Z. Zeng, Yi-Xin Li, Rui Xie et al. · 1 citation
Preprint Aug 2026

Qwen-CUA: Native Computer Use for (almost) Everything

Qwen-CUA is introduced, a native computer-use agent with a 397B-A17B Qwen mixture-of-experts backbone that outperforms Qwen3.7 and remains competitive with leading proprietary systems, and scalable verifiable interaction and hybrid tool use as key directions.

Dunjie Lu, Shuai Bai, Tianyi Bai et al. · 2 citations

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