الباحثون

Bin Chen

المنشورات 10

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IronMan: Information-Constrained Video-Action Learning for Robot Manipulation

Yuanshuo Zhang, Wenzhe Zhao, Zixing Lei وآخرون · 2026

Video Action Models (VAMs) couple visual dynamics modeling with action generation for robot manipulation. However, video representations are not naturally suited to action generation, as exposing the action policy to excessive visual detail can impair its generalization ability. Therefore, we introduce IronMan (Informa …

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MoTIF-X: A Multimodal Tokenized Framework for Interpretable and Extensible Molecular Representation Learning

Molecular representation learning is central to computer-aided drug discovery. Molecular graphs, SMILES strings, and 3D conformations provide complementary structural information, yet many multimodal approaches encode these views independently and align them only at a later stage, limiting fine-grained cross-modal inte …

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PrecogUI: Proactive GUI Agents via Pre-cognitive Simulation and Experience Retrieval

Bin Kang, Jiarui Ouyang, Li Jiang وآخرون · 2026

Existing reactive Graphical User Interface (GUI) agents often fail in long-horizon, dynamic scenarios, where unexpected disturbances trigger attention-diverting and cascading failures. To address this, we propose PrecogUI, a pre-cognitive architecture that shifts the paradigm from reactive execution to proactive decisi …

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Dense Is Not Enough: Hierarchical Supervision Allocation for Long-Horizon On-Policy Distillation

Yuhao Sun, Binrui Wu, Zhuoer Xu وآخرون · 2026

On-policy distillation (OPD) transfers the capabilities of a large language model to a smaller student by providing teacher supervision on the student's own rollouts. In long-horizon agentic tasks, however, uniform token-level matching can allocate supervision poorly: a large local discrepancy need not improve future b …

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IndustryLLM: Failure-Driven LLM Training for Industrial Procurement

Liang Ding, Zhiang Xu, Yuyang Sheng وآخرون · 2026

Industrial procurement requires language models to bridge informal buyer jargon, sparse marketplace attributes, and authoritative engineering standards under strict safety tolerances. We present IndustryLLM, an open-weight industrial language model trained from Qwen3.5-35B-A3B-Base (35B total parameters with ~3B activa …

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Strip Convolution and Direction-Aware Exclusion Loss for Oriented Ship Detection

Bin Chen, Yuanyuan Liu, Peng Yang وآخرون · 2026

Oriented ship detection in very high resolution (VHR) remote sensing imagery remains challenging due to elongated hull geometry and dense target distributions in complex port scenes. Existing methods typically address geometric representation and duplicate suppression separately. To jointly tackle these issues, we prop …

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From Bits to Beliefs: Recoverable Semantic Fingerprints for Black-Box Verification of Large Language Models

Jiaxin Hong, Yuxin Peng, Hongyao Yu وآخرون · 2026

Open-weight large language models (LLMs) can be copied, modified, and redeployed behind black-box APIs, making post-release ownership verification difficult. Existing black-box fingerprints often rely on secret query-key pairs that reproduce predefined responses, and can therefore be easily disrupted by fine-tuning, pr …

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Behavior2Value: Benchmarking and Empowering LLMs for Consumer Value Measurement from E-commerce Behaviors

Peixuan Hou, Bin Chen, Li He وآخرون · 2026

Human values are deep motivational orientations that shape human behaviors. In e-commerce, they reveal the stable drivers behind users' purchase decisions. Compared with short-term interests, consumer values better explain how users evaluate products before purchase. However, consumer values are often implicit in compl …

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