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arXiv:2602.16986v1 Announce Type: new Abstract: Learning from user interaction history through sequential models has become a cornerstone of large-scale recommender systems. Recent advances in large...
arXiv:2602.16987v1 Announce Type: new Abstract: As artificial intelligence (AI) capabilities advance rapidly, frontier models increasingly demonstrate systematic deception and scheming, complying with safety protocols during...
arXiv:2602.16989v1 Announce Type: new Abstract: We present a low-cost retrieval system for the WSDM Cup 2026 multilingual retrieval task, where English queries are used to...
arXiv:2602.16990v1 Announce Type: new Abstract: Most recommendation benchmarks evaluate how well a model imitates user behavior. In financial advisory, however, observed actions can be noisy...
arXiv:2602.16994v1 Announce Type: new Abstract: Multi-path speculative decoding accelerates lossless sampling from a target model by using a cheaper draft model to generate a draft...
arXiv:2602.16997v1 Announce Type: new Abstract: User stories are one of the most widely used artifacts in the software industry to define functional requirements. In parallel,...
arXiv:2602.16998v1 Announce Type: new Abstract: We study preference learning through recommendations in multi-agent game settings, where a moderator repeatedly interacts with agents whose utility functions...
arXiv:2602.17001v1 Announce Type: new Abstract: Natural Language Querying for Time Series Databases (NLQ4TSDB) aims to assist non-expert users retrieve meaningful events, intervals, and summaries from...
arXiv:2602.17002v1 Announce Type: new Abstract: This work presents a Total Lagrangian finite element formulation for deformable body dynamics. We employ the TL-FEA framework to simulate...
arXiv:2602.17003v1 Announce Type: new Abstract: Large language models have advanced web agents, yet current agents lack personalization capabilities. Since users rarely specify every detail of...
arXiv:2602.17005v1 Announce Type: new Abstract: Fictional character representations reflect social norms and biases. Women are relatively underrepresented in television and film, irrespective of genre. In...
arXiv:2602.17009v1 Announce Type: new Abstract: Coordinating actions is the most fundamental form of cooperation in multi-agent reinforcement learning (MARL). Successful decentralized decision-making often depends not...
arXiv:2602.17011v1 Announce Type: new Abstract: High-density biosignal recordings are critical for neural decoding and clinical monitoring, yet real-world deployments often rely on low-density (LD) montages...
arXiv:2602.17013v1 Announce Type: new Abstract: We establish a rigorous connection between pathwise (reparameterization) and score-function (Malliavin) gradient estimators by showing that both arise from the...
arXiv:2602.17015v1 Announce Type: new Abstract: A fair and fast matchmaking system is an important component of modern multiplayer online games, directly impacting player retention and...
arXiv:2602.17016v1 Announce Type: new Abstract: Automated formalization of mathematics enables mechanical verification but remains limited to isolated theorems and short snippets. Scaling to textbooks and...
arXiv:2602.17017v1 Announce Type: new Abstract: Enterprises increasingly need AI systems that can answer sales-leader questions over live, customized CRM data, but most available models do...
arXiv:2602.17018v1 Announce Type: new Abstract: The adoption of third-party libraries has become integral to modern software development, leading to large ecosystems such as PyPI, NPM,...
arXiv:2602.17019v1 Announce Type: new Abstract: This paper investigates the joint optimization of trajectory, user scheduling, and time-slot duration in unmanned aerial vehicle (UAV)-assisted wireless communication...
arXiv:2602.17022v1 Announce Type: new Abstract: Conversational agents powered by large language models (LLMs) with tool integration achieve strong performance on fixed task-oriented dialogue datasets but...
arXiv:2602.17025v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) is effective for training language models on complex reasoning. However, since the objective is defined...
arXiv:2602.17027v1 Announce Type: new Abstract: Scientific discovery pipelines typically involve complex, rigid, and time-consuming processes, from data preparation to analyzing and interpreting findings. Recent advances...
arXiv:2602.17028v1 Announce Type: new Abstract: Detecting anomalies in time-series data is critical in domains such as industrial operations, finance, and cybersecurity, where early identification of...
arXiv:2602.17030v1 Announce Type: new Abstract: As agentic AI becomes increasingly involved in creative production, documenting authorship has become critical for artists, collectors, and legal contexts....