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arXiv:2602.10053v2 Announce Type: replace Abstract: Standard models of bounded rationality typically assume agents either possess accurate knowledge of the population's reasoning abilities (Cognitive Hierarchy) or...
arXiv:2602.09829v2 Announce Type: replace Abstract: Large Language Models (LLMs) are reshaping recommender systems by leveraging extensive world knowledge and semantic reasoning to interpret user intent....
arXiv:2602.09744v2 Announce Type: replace Abstract: Latent reasoning has emerged as a promising paradigm for sequential recommendation, enabling models to capture complex user intent through multi-step...
arXiv:2602.09725v2 Announce Type: replace Abstract: Remote KV cache reuse fetches KV cache for identical contexts from remote storage, avoiding recomputation, accelerating LLM inference. While it...
arXiv:2602.09523v2 Announce Type: replace Abstract: We present Singpath-VL, a vision-language large model, to fill the vacancy of AI assistant in cervical cytology. Recent advances in...
arXiv:2602.09477v2 Announce Type: replace Abstract: Digital histopathology whole slide images (WSIs) provide gigapixel-scale high-resolution images that are highly useful for disease diagnosis. However, digital histopathology...
arXiv:2602.09467v2 Announce Type: replace Abstract: Traceability links are key information sources for software developers, connecting software artifacts (e.g., linking requirements to the corresponding source code)....
arXiv:2602.09387v2 Announce Type: replace Abstract: Learning effective feature interactions is central to modern recommender systems, yet remains challenging in industrial settings due to sparse multi-field...
arXiv:2602.09369v2 Announce Type: replace Abstract: The rapid expansion of GPU-accelerated computing has enabled major advances in large-scale artificial intelligence (AI), while heightening concerns about how...
arXiv:2602.09349v2 Announce Type: replace Abstract: Participatory budgeting (PB) is a democratic paradigm for deciding the funding of public projects given the residents' preferences, which has...
arXiv:2602.09319v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) has become a cornerstone of knowledge-intensive applications, including enterprise chatbots, healthcare assistants, and agentic memory management. However,...
arXiv:2602.09316v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) based Large Language Models (LLMs) have achieved superior performance, yet the massive memory overhead caused by storing multiple...
arXiv:2602.09255v2 Announce Type: replace Abstract: Mobile robots are often deployed over long durations in diverse open, dynamic scenes, including indoor setting such as warehouses and...
arXiv:2602.09070v2 Announce Type: replace Abstract: Synthesizing coherent soundtracks for long-form videos remains a formidable challenge, currently stalled by three critical impediments: computational scalability, temporal coherence,...
arXiv:2602.09013v2 Announce Type: replace Abstract: Multi-finger robotic hand manipulation and grasping are challenging due to the high-dimensional action space and the difficulty of acquiring large-scale...
arXiv:2602.08930v3 Announce Type: replace Abstract: Open-vocabulary keyword spotting (OV-KWS) enables personalized device control via arbitrary voice commands. Recently, researchers have explored using audio-text joint embeddings,...
arXiv:2602.08907v2 Announce Type: replace Abstract: We study a setting where the goal is to learn a target function f(x) with respect to a target distribution...
arXiv:2602.08751v2 Announce Type: replace Abstract: Current biological AI models lack interpretability -- their internal representations do not correspond to biological relationships that researchers can examine....
arXiv:2602.08711v2 Announce Type: replace Abstract: This paper proposes Omni Dense Captioning, a novel task designed to generate continuous, fine-grained, and structured audio-visual narratives with explicit...
arXiv:2602.08615v2 Announce Type: replace Abstract: While generative models have become powerful tools for image synthesis, they are typically optimized for executing carefully crafted textual prompts,...
arXiv:2602.08535v2 Announce Type: replace Abstract: Generative modeling typically seeks the path of least action via deterministic flows (ODE). While effective for in-distribution tasks, we argue...
arXiv:2602.08520v3 Announce Type: replace Abstract: Modern large language models (LLMs) are often evaluated and deployed under a one-shot, greedy inference protocol, especially in professional settings...
arXiv:2602.08517v2 Announce Type: replace Abstract: Tensor is the most basic and essential data structure of nowadays artificial intelligence (AI) system. The natural properties of Tensor,...
arXiv:2602.08449v2 Announce Type: replace Abstract: Safety evaluation for advanced AI systems implicitly assumes that behavior observed under evaluation predicts behavior in deployment. This assumption becomes...