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arXiv:2602.10431v3 Announce Type: replace Abstract: Large language models (LLMs) demand substantial computational and memory resources, posing challenges for efficient deployment. Two complementary approaches have emerged...
arXiv:2602.10606v3 Announce Type: replace Abstract: Generative recommendation models sequence generation to produce items end-to-end, but training from behavioral logs often provides weak supervision on underlying...
arXiv:2602.10953v2 Announce Type: replace Abstract: Diffusion Language Models (DLMs) generate text by iteratively denoising a masked sequence, repeatedly deciding which positions to commit at each...
arXiv:2602.11020v2 Announce Type: replace Abstract: We study same-source multi-view learning and adversarial robustness for next-day direction prediction using two deterministic, window-aligned image views derived from...
arXiv:2602.11961v2 Announce Type: replace Abstract: Open large language models (LLMs) have demonstrated improving multilingual capabilities in recent years. In this paper, we present a study...
arXiv:2602.12259v2 Announce Type: replace Abstract: Explaining observed phenomena through symbolic, interpretable formulas is a fundamental goal of science. Recently, large language models (LLMs) have emerged...
arXiv:2602.12304v2 Announce Type: replace Abstract: Existing mainstream video customization methods focus on generating identity-consistent videos based on given reference images and textual prompts. Benefiting from...
arXiv:2602.12635v2 Announce Type: replace Abstract: As LLMs scale, low-bit floating-point formats like MXFP and NVFP4 offer new opportunities for precision and efficiency. In this work,...
arXiv:2602.13477v2 Announce Type: replace Abstract: As Large Language Model (LLM) agents become more capable, their coordinated use in the form of multi-agent systems is anticipated...
arXiv:2602.13551v2 Announce Type: replace Abstract: Reward models (RMs) play a central role throughout the language model (LM) pipeline, particularly in non-verifiable domains. However, the dominant...
arXiv:2602.13769v2 Announce Type: replace Abstract: Automating scientific discovery in complex, experiment-driven domains requires more than iterative mutation of programs; it demands structured hypothesis management, environment...
arXiv:2602.13920v3 Announce Type: replace Abstract: Recent advances in agent-mediated systems have enabled a new paradigm of social network simulation, where AI agents interact with human-like...
arXiv:2602.14697v3 Announce Type: replace Abstract: Building agentic systems that can autonomously self-improve from experience is a longstanding goal of AI. Large language models (LLMs) today...
arXiv:2602.14903v2 Announce Type: replace Abstract: Chain-of-thought (CoT) prompting is a de-facto standard technique to elicit reasoning-like responses from large language models (LLMs), allowing them to...
arXiv:2602.16057v2 Announce Type: replace Abstract: Railway crossings present complex safety challenges where driver behavior varies by location, time, and conditions. Traditional approaches analyze crossings individually,...
arXiv:2602.16291v3 Announce Type: replace Abstract: Just as the $\lambda$-calculus uses three primitives (abstraction, application, variable) as the foundation of functional programming, inheritance-calculus uses three primitives...
arXiv:2602.16642v3 Announce Type: replace Abstract: Neural Collapse (NC) refers to the emergence of highly symmetric geometric structures in the representations of deep neural networks during...
arXiv:2602.16852v2 Announce Type: replace Abstract: Meenzerisch, the dialect spoken in the German city of Mainz, is also the traditional language of the Mainz carnival, a...
arXiv:2602.16893v2 Announce Type: replace Abstract: Families raising children with ADHD often experience heightened stress and reactive parenting. While digital interventions promise personalization, many remain one-size-fits-all...
arXiv:2602.16898v3 Announce Type: replace Abstract: Task planning for robotic manipulation with large language models (LLMs) is an emerging area. Prior approaches rely on specialized models,...
arXiv:2602.16900v2 Announce Type: replace Abstract: Peer health posts surface new uncertainties, such as questions and concerns for readers. Prior work focused primarily on improving relevance...
arXiv:2602.17484v2 Announce Type: replace Abstract: Image Copy Detection (ICD) aims to identify manipulated content between image pairs through robust feature representation learning. While self-supervised learning...
arXiv:2602.17784v2 Announce Type: replace Abstract: Mineral prospectivity mapping requires synthesizing heterogeneous geological knowledge, including textual deposit models and geospatial datasets, to identify regions likely to...
arXiv:2602.17849v2 Announce Type: replace Abstract: Training and serving Large Language Models (LLMs) relies heavily on parallelization and collective operations, which are frequently bottlenecked by network...