Stay updated with the latest research and technology news
arXiv:2601.17434v1 Announce Type: new Abstract: Artificial intelligence (AI) and large language models (LLMs) are reshaping education, with virtual avatars emerging as digital teachers capable of...
arXiv:2601.17435v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have enabled the development of increasingly complex agentic and multi-agent systems capable of...
arXiv:2601.17438v1 Announce Type: new Abstract: Generative recommendation has recently emerged as a transformative paradigm that directly generates target items, surpassing traditional cascaded approaches. It typically...
arXiv:2601.17440v1 Announce Type: new Abstract: Humanoid robots hold great potential for diverse interactions and daily service tasks within human-centered environments, necessitating controllers that seamlessly integrate...
arXiv:2601.17441v1 Announce Type: new Abstract: On-device large language models commonly employ task-specific adapters (e.g., LoRAs) to deliver strong performance on downstream tasks. While storing all...
arXiv:2601.17442v1 Announce Type: new Abstract: This work introduces a novel approach for the joint selection of model structure and parameter learning for nonlinear dynamical systems...
arXiv:2601.17443v1 Announce Type: new Abstract: Large language models (LLMs) often rely on user-specific memories distilled from past interactions to enable personalized generation. A common practice...
arXiv:2601.17447v1 Announce Type: new Abstract: Developing students as well-rounded professionals is increasingly important for our modern society. Although there is a great consensus that technical...
arXiv:2601.17449v1 Announce Type: new Abstract: Graph neural networks (GNNs) have been widely used in various graph machine learning scenarios. Existing literature primarily assumes well-annotated training...
arXiv:2601.17450v1 Announce Type: new Abstract: Artificial Intelligence (AI) compilers are critical for efficiently deploying AI models across diverse hardware platforms. However, they remain prone to...
arXiv:2601.17452v2 Announce Type: new Abstract: We study dissipative weak (DW) solutions of the Euler equations of gas dynamics using the first-, second-, third-, fifth-, seventh-,...
arXiv:2601.17454v1 Announce Type: new Abstract: Centralized value learning is often assumed to improve coordination and stability in multi-agent reinforcement learning, yet this assumption is rarely...
arXiv:2601.17458v1 Announce Type: new Abstract: Surgical emergencies often trigger acute cognitive overload in novice physicians, impairing their decision-making under pressure. Although Virtual Reality-based Stress Inoculation...
arXiv:2601.17464v1 Announce Type: new Abstract: Robust output regulation for linear time-varying systems has remained an open problem for decades. To address this, we propose intrinsic...
arXiv:2601.17467v1 Announce Type: new Abstract: Large reasoning models (LRMs) often generate long, seemingly coherent reasoning traces yet still produce incorrect answers, making hallucination detection challenging....
arXiv:2601.17468v1 Announce Type: new Abstract: Single Image Reflection Separation (SIRS) disentangles mixed images into transmission and reflection layers. Existing methods suffer from transmission-reflection confusion under...
arXiv:2601.17469v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have shown remarkable capabilities in learning from graph-structured data with various applications such as social analysis...
arXiv:2601.17470v1 Announce Type: new Abstract: Shadow removal under diverse lighting conditions requires disentangling illumination from intrinsic reflectance, a challenge compounded when physical priors are not...
arXiv:2601.17471v1 Announce Type: new Abstract: Continuous fuzzing platforms such as OSS-Fuzz uncover large numbers of vulnerabilities, yet the subsequent repair process remains largely manual. Unfortunately,...
arXiv:2601.17472v1 Announce Type: new Abstract: Cross-domain recommendation (CDR) has been increasingly explored to address data sparsity and cold-start issues. However, recent approaches typically disentangle domain-invariant...
arXiv:2601.17473v1 Announce Type: new Abstract: This paper considers the development of an AI-based provably-correct mathematical proof tutor. While Large Language Models (LLMs) allow seamless communication...
arXiv:2601.17476v1 Announce Type: new Abstract: Peer review determines which scholarship is legitimized; however, review biases often disadvantage scholarship that diverges from the norm. Human-Computer Interaction...
arXiv:2601.17480v1 Announce Type: new Abstract: Fine-tuning Large Language Models (LLMs) on sensitive datasets carries a substantial risk of unintended memorization and leakage of Personally Identifiable...
arXiv:2601.17481v1 Announce Type: new Abstract: Conversational AI systems require guardrails to prevent harmful outputs, yet existing approaches use static rules that cannot adapt to new...