Fast surrogate models for expensive simulations are now essential across the sciences, yet they typically operate as black boxes. We present \texttt{GWAgent}, a large language model (LLM)-based workflow that constructs interpretable analytic surrogates directly from simulation data. Surrogate modeling is well suited to...
Tousif Islam, Digvijay Wadekar, Tejaswi Venumadhav et al.· 0 citations
Modern gravitational wave astronomy relies on modeling tasks that often require months of graduate-level effort, including building fast waveform surrogates from expensive numerical relativity simulations, modeling orbital dynamics of black holes, fitting merger remnant properties and constructing template banks. These...
In this study, we tackle Generalized Category Discovery (GCD) via a Relational Retrieval perspective, explicitly coupling labeled and unlabeled data through bidirectional knowledge transfer. While existing methods treat these sources separately, missing valuable interaction opportunities, we propose Relational Pattern...
Yulin Xu, Chunqi Guo, Yuanzhen Shuai et al.· 0 citations
To the authors' knowledge, this is the first end-to-end autonomous attack-remediation demonstration on bare-metal industrial devices, establishing controlled feasibility - not zero-day discovery or production-OT transfer.
Adel Elzemity, Budi Arief, Shujun Li et al.· arXiv.org· 1 citation
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Recent advancements in Large Language Models (LLMs) have demonstrated significant potential across software engineering tasks, including software design, an area traditionally regarded as highly dependent on human expertise and judgment. However, limited research has examined how LLMs are used in software design, aswel...
Yifei Wang, Ruiyin Li, Peng Liang et al.· 0 citations
Human visual preferences are inherently multi-dimensional, encompassing aesthetics, detail fidelity, and semantic alignment. However, existing datasets provide only single, holistic annotations, resulting in severe label noise: images that excel in some dimensions but are deficient in others are simply marked as winner...
Xinxin Liu, Ming Li, Zonglin Lyu et al.· 0 citations
Automating repository-level software engineering tasks is a foundational challenge for autonomous code agents, largely due to the difficulty of configuring executable environments. However, manual configuration remains a labor-intensive bottleneck, necessitating a transition toward fully automated environment configura...
Renhong Huang, Dongdong Hua, Yifei Sun et al.· 0 citations
This paper introduces an Neighborhood-Aware Anchor Pruning (NAAP) strategy, which evaluates anchor importance via weighted neighborhood feature aggregation and then merges low-contribution anchors into salient neighbors, yielding a compact yet geometry-consistent anchor set.
X. Deng, Xian-Dong Meng, Hengyu Man et al.· arXiv.org· 0 citations
Hybrid aerial--ground robots can use thrust to cross obstacles that impede wheel-driven motion, but deciding how much thrust to apply during contact remains challenging. We present an energy-aware reinforcement learning framework that jointly commands wheels, tilt servos and propellers through a single continuous polic...
Jiaxing Li, Ishaan Bhimwal, Wen Tian et al.· 0 citations
SAIL is a framework that reframes robot imitation as an iterative refinement problem capable of scaling with test-time compute, and utilizes Monte Carlo Tree Search, where each node is a complete trajectory and edges correspond to trajectory refinements.
Full-stack human-robot collaboration (HRC) can become brittle when replacing a planner, partner model, coordination policy, or controller changes the physical meaning of cross-layer signals. We introduce C2C, an object-centric cognition-to-control architecture that preserves these meanings through physical contracts. R...
Hao Zhang, Yisen Li, Ruize Geng et al.· 0 citations
Test-Time Scaling has shown notable efficacy in addressing complex problems through scaling inference compute. However, within Large Audio-Language Models (LALMs), an unintuitive phenomenon exists: post-training models for structured reasoning trajectories results in marginal or even negative gains compared to post-tra...
Ruixiang Mao, Xiangnan Ma, Dan Chen et al.· 0 citations
With $2.1 million funding from Google.org, the open-source Public Transit Intelligence Hub will unify public transit monitoring, operations, and passenger communication.
Professor Sherry Turkle’s new book, “Artificial Intimacy,” offers a withering critique of chatbots and the antisocial dynamics she believes they encourage.
