Large Language Models (LLMs) have shown promising capabilities in scientific reasoning, yet scientific discovery ultimately requires deriving precise laws directly from observational data, known as Symbolic Regression (SR). This poses a challenge for LLMs due to the gap between probabilistic text generation and the exa...
Jun Yao, Ying-Fan Hua, Rui-Kun Li et al.· 0 citations
StraTA is a simple framework that introduces an explicit trajectory-level strategy into agentic reinforcement learning (RL) and trains strategy generation and action execution jointly with a hierarchical GRPO-style rollout design, further enhanced by diverse strategy rollout and critical self-judgment.
Xiangyuan Xue, Yifan Zhou, Zidong Wang et al.· arXiv.org· 1 citation
An injectively aligned leave-one-cell-out protocol over support x operation grids and SO-OPF, a readout that factors cell energy into support salience and a competitive operation posterior, and a readout that factors cell energy into support salience and a competitive operation posterior are introduced.
Zhong-Yao Wang, Wan-Li Ouyang, Tao-Yong Cui et al.· 0 citations
Powder X-ray diffraction (PXRD) is the routine probe of crystalline matter, yet its analysis is the rate-limiting step as laboratories automate acquisition. Deep-learning analyzers excel on simulated patterns and degrade on measured ones. This simulation-to-real gap is structural, not additive: synthetic denoising give...
Shaoguang Wang, Weiyu Guo, Ben Fei et al.· 0 citations
World modeling enables intelligence to anticipate consequences, guide interventions, and learn from interaction. Yet predictive models remain domain-specific: can a common learning principle support world modeling across radically different systems? We introduce JEPA-Anything, a domain-agnostic framework based on ortho...
Tao-Yong Cui, Zhong-Yao Wang, Xin-Yue Xu et al.· 0 citations
CENO is introduced, a family of long-context generative genomic world models designed to preserve local DNA grammar while extending usable context to regulatory and chromatin scales and provides a genome-scale sequence world-model framework for sequence interpretation, evolutionary reasoning, gene-scale reconstruction...
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.· arXiv.org· 0 citations
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.
Jia-Qi Wei, Xiang Zhang, Yue-Jin Yang et al.· 0 citations
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.
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.
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 clo...
Haobo Wang, Baoli Sun, Anqi Zou et al.· 0 citations
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