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arXiv:2601.17408v1 Announce Type: new Abstract: Source-Free Domain Adaptation (SFDA) is an emerging area of research that aims to adapt a model trained on a labeled...
arXiv:2601.17412v1 Announce Type: new Abstract: We propose a novel Unmanned Aerial Vehicles (UAV) assisted creative capture system that leverages diffusion models to interpret high-level natural...
arXiv:2601.17413v1 Announce Type: new Abstract: AI agents are increasingly used in software development, yet their interaction with CI/CD configurations is not well studied. We analyze...
arXiv:2601.17414v1 Announce Type: new Abstract: The proliferation of Internet of Things (IoT) devices has created unprecedented opportunities for remote monitoring and control applications across various...
arXiv:2601.17417v1 Announce Type: new Abstract: Detecting misogynistic hate speech is a difficult algorithmic task. The task is made more difficult when decision criteria for what...
arXiv:2601.17418v1 Announce Type: new Abstract: Mobile graphical user interface (GUI) agents are designed to automate everyday tasks on smartphones. Recent advances in large language models...
arXiv:2601.17420v1 Announce Type: new Abstract: Existing works of reasoning segmentation often fall short in complex cases, particularly when addressing complicated queries and out-of-domain images. Inspired...
arXiv:2601.17421v1 Announce Type: new Abstract: The emergence of discourse-like tokens such as "wait" and "therefore" in large language models (LLMs) has offered a unique window...
arXiv:2601.17422v1 Announce Type: new Abstract: Modular composition is the problem of computing the composition of two univariate polynomials modulo a third one. For a long...
arXiv:2601.17423v1 Announce Type: new Abstract: This paper optimizes the fronthaul bit allocation in massive multi-user multiple-input multiple-output (MU-MIMO) systems operating with limited-capacity fronthaul links. We...
arXiv:2601.17425v1 Announce Type: new Abstract: This paper considers the scheduling of stochastic jobs on parallel identical machines to minimize the expected total weighted completion time....
arXiv:2601.17426v1 Announce Type: new Abstract: Human logic has gradually shifted from intuition-driven inference to rigorous formal systems. Motivated by recent advances in large language models...
arXiv:2601.17428v1 Announce Type: new Abstract: Curriculum learning has demonstrated substantial effectiveness in robot learning. However, it still faces limitations when scaling to complex, wide-ranging task...
arXiv:2601.17430v1 Announce Type: new Abstract: We study the problem of identifying an anomalous subset of streams under correlated noise, motivated by monitoring and security in...
arXiv:2601.17431v1 Announce Type: new Abstract: The adoption of Large Language Models (LLMs) in scientific writing promises efficiency but risks introducing informational entropy. While "hallucinated papers"...
arXiv:2601.17432v1 Announce Type: new Abstract: We introduce an efficient algorithmic procedure for implementing the direct formula that represents the product of splines in the B-spline...
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...