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arXiv:2602.21072v1 Announce Type: new Abstract: Off-dynamics offline reinforcement learning (RL) aims to learn a policy for a target domain using limited target data and abundant...
arXiv:2602.21073v1 Announce Type: new Abstract: Active automata learning (AAL) under a Minimally Adequate Teacher (MAT) has been successfully used to infer a regular language through...
arXiv:2602.21074v1 Announce Type: new Abstract: The analyzability of hybrid software, which integrates both classical and quantum components, is a key factor in ensuring its maintainability...
arXiv:2602.21078v1 Announce Type: new Abstract: Federated Semi-Supervised Learning (FSSL) aims to collaboratively train a global model across clients by leveraging partially-annotated local data in a...
arXiv:2602.21081v1 Announce Type: new Abstract: Vision Transformers (ViTs) have demonstrated remarkable potential in image processing tasks by utilizing self-attention mechanisms to capture global relationships within...
arXiv:2602.21082v1 Announce Type: new Abstract: Customer-provided reviews have become an important source of information for business owners and other customers alike. However, effectively analyzing millions...
arXiv:2602.21087v1 Announce Type: new Abstract: We present an exact and efficient algorithm for computing the Reeb space of a bivariate PL map. The Reeb space...
arXiv:2602.21088v1 Announce Type: new Abstract: We prove a space-space trade-off for directed $st$-connectivity in the catalytic space model. For any integer $k \leq n$, we...
arXiv:2602.21089v1 Announce Type: new Abstract: We develop catalytic algorithms for fundamental problems in algorithm design that run in polynomial time, use only $\mathcal{O}(\log(n))$ workspace, and...
arXiv:2602.21092v1 Announce Type: new Abstract: Curvature notions on graphs provide a theoretical description of graph topology, highlighting bottlenecks and denser connected regions. Artifacts of the...
arXiv:2602.21098v1 Announce Type: new Abstract: Understanding the locations of occupants in a commercial built environment is critical for realizing energy savings by delivering lighting, heating,...
arXiv:2602.21099v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown great potential for enhancing recommender systems through their extensive world knowledge and reasoning capabilities....
arXiv:2602.21100v1 Announce Type: new Abstract: Reconstructing high-fidelity 3D head geometry from images is critical for a wide range of applications, yet existing methods face fundamental...
arXiv:2602.21101v1 Announce Type: new Abstract: Fast-flying aerial robots promise rapid inspection under limited battery constraints, with direct applications in infrastructure inspection, terrain exploration, and search...
arXiv:2602.21103v1 Announce Type: new Abstract: Advanced reasoning typically requires Chain-of-Thought prompting, which is accurate but incurs prohibitive latency and substantial test-time inference costs. The standard...
arXiv:2602.21104v1 Announce Type: new Abstract: We revisit the central online problem of ski rental in the "algorithms with predictions" framework from the point of view...
arXiv:2602.21105v1 Announce Type: new Abstract: The boundary representation (B-rep) models a 3D solid as its explicit boundaries: trimmed corners, edges, and faces. Recovering B-rep representation...
arXiv:2602.21113v1 Announce Type: new Abstract: This survey discusses recent advancements in SYCL compiler implementations, one of the crucial aspects of compiler construction for heterogeneous computing...
arXiv:2602.21114v1 Announce Type: new Abstract: This paper introduces delay-alignment modulation (DAM) for secure integrated sensing and communication (ISAC). Due to the broadcast nature of multi-user...
arXiv:2602.21119v1 Announce Type: new Abstract: Multi-agent deep Reinforcement Learning (RL) has made significant progress in developing intelligent game-playing agents in recent years. However, the efficient...
arXiv:2602.21127v1 Announce Type: new Abstract: Large language model (LLM) agents are rapidly becoming trusted copilots in high-stakes domains like software development and healthcare. However, this...
arXiv:2602.21133v1 Announce Type: new Abstract: Vector-quantized representations enable powerful discrete generative models but lack semantic structure in token space, limiting interpretable human control. We introduce...
arXiv:2602.21136v1 Announce Type: new Abstract: Qualitative insights from user experiences are critical for informing product and policy decisions, but collecting such data at scale is...
arXiv:2602.21137v1 Announce Type: new Abstract: Understanding the complex, multi-agent dynamics of urban traffic remains a fundamental challenge for video language models. This paper introduces Urban...