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Author

Wanli Ouyang

5 papers indexed here

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SciOrch: Learning to Orchestrate Expert LLMs for Solving Frontier Multimodal Scientific Reasoning Tasks

SciOrch is presented, a framework that trains a lightweight 8B model to orchestrate frontier LLMs for scientific reasoning, and attains the best accuracy on both SGI and SFE with less than half the API cost of typical multi-agent methods.

Jingru Guo, Xiangyuan Xue, Lian Zhang et al. · 0 citations

When LLM Meets Tree Search: A Systematic View of Inference as Search in Large Language Models

This survey systematizes recent progress in tree-search-based reasoning, viewing inference as instance-specific optimization rather than decoding, and introduces a Unified Design Space spanning search topology, evaluation signals, and control dynamics to unify a fragmented literature.

Jiaqi Wei, Xiang Zhang, Yue-Jin Yang et al. · 0 citations
Preprint Aug 2026

Video-DeepResearch: Towards the Next-Generation Multimodal Deepresearch Agent

Video-DR is introduced, featuring a decoupled perception-exploration pipeline with stage-wise tool unlocking that compels exhaustive cross-frame visual grounding prior to web retrieval, enabling autonomous exploration that breaks the imitation-learning ceiling.

Zhen Fang, Yu Zeng, Wen-Xuan Huang et al. · 1 citation · ⚡1
Preprint Aug 2026

Orthogonal JEPA: Factorized Predictive States for Latent World Models

Method, a latent world-modeling framework based on orthogonal predictive factorization, is introduced, a latent world-modeling framework based on orthogonal predictive factorization that can be used by a readout, decoder, planner, or autoregressive rollout of an underlying system.

Taoyong Cui, Pheng-Ann Heng, Wanli Ouyang · 0 citations
Preprint Jul 2026

LabRobFail: A Benchmark for Robotic Failure Analysis in Chemical Self-driving Laboratory

LabRobFail, a failure-centric framework for learning and evaluating robotic failure analysis in chemical laboratories, and LabRobFail-VLM, a domain-specialized vision-language model that generates structured failure diagnoses and recovery instructions, demonstrate the value of fine-grained failure understanding for closed-loop recovery and reliable laboratory autonomy.

Haobo Wang, Baoli Sun, Anqi Zou et al. · 0 citations

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