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arXiv:2601.18253v1 Announce Type: new Abstract: Accurate evaluation of user satisfaction is critical for iterative development of conversational AI. However, for open-ended assistants, traditional A/B testing...
arXiv:2601.18255v1 Announce Type: new Abstract: Continual learning in Large Language Models (LLMs) faces the critical challenge of balancing stability (retaining old knowledge) and plasticity (learning...
arXiv:2601.18256v1 Announce Type: new Abstract: Wi-Fi access points have been widely deployed in homes, offices, and public spaces. Some APs allow users to adjust the...
arXiv:2601.18260v1 Announce Type: new Abstract: Automated patient positioning plays an important role in optimizing scanning procedure and improving patient throughput. Leveraging depth information captured by...
arXiv:2601.18261v1 Announce Type: new Abstract: Catastrophic forgetting impairs the continuous learning of large language models. We propose Fisher-Guided Gradient Masking (FGGM), a framework that mitigates...
arXiv:2601.18263v1 Announce Type: new Abstract: Aerial images play a vital role in urban planning and environmental preservation, as they consist of various structures, representing different...
arXiv:2601.18264v1 Announce Type: new Abstract: Universal approximation theory offers a foundational framework to verify neural network expressiveness, enabling principled utilization in real-world applications. However, most...
arXiv:2601.18267v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) shows promise for enterprise knowledge work, yet it often underperforms in high-stakes decision settings that require deep...
arXiv:2601.18271v1 Announce Type: new Abstract: In some areas of computing, natural language processing and information science, progress is made by sharing datasets and challenging the...
arXiv:2601.18274v1 Announce Type: new Abstract: In recent years, Spiking Neural Networks (SNNs) have achieved remarkable progress, with Spiking Transformers emerging as a promising architecture for...
arXiv:2601.18275v1 Announce Type: new Abstract: Powered by large language models, a new genre of multi-agent social platforms has emerged. Apps such as Social.AI deploy numerous...
arXiv:2601.18278v1 Announce Type: new Abstract: In many scientific and data-driven applications, machine learning models are increasingly used as measurement instruments, rather than merely as predictors...
arXiv:2601.18280v1 Announce Type: new Abstract: Optoacoustic (OA) imaging has emerged as a powerful investigation tool, with demonstrated applicability in oncology, neuroscience, and cardiovascular biology. However,...
arXiv:2601.18281v1 Announce Type: new Abstract: End-to-end Spoken Language Models (SLMs) hold great potential for paralinguistic perception, and numerous studies have aimed to enhance their capabilities,...
arXiv:2601.18282v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated remarkable capabilities in function calling for autonomous agents, yet current mechanisms lack explicit reasoning...
arXiv:2601.18284v1 Announce Type: new Abstract: Traffic congestion remains a major challenge for urban transportation, leading to significant economic and environmental impacts. Traffic Signal Control (TSC)...
arXiv:2601.18285v1 Announce Type: new Abstract: Large language model (LLM)-based agents have been successfully deployed in many tool-augmented settings, but their scalability is fundamentally constrained by...
arXiv:2601.18289v1 Announce Type: new Abstract: Quest2ROS2 is an open-source ROS2 framework for bi-manual teleoperation designed to scale robot data collection. Extending Quest2ROS, it overcomes workspace...
arXiv:2601.18292v1 Announce Type: new Abstract: In recent years, safety risks associated with large language models have become increasingly prominent, highlighting the urgent need to mitigate...
arXiv:2601.18294v1 Announce Type: new Abstract: Cooperative control of groups of autonomous vehicles (AVs), i.e., platoons, is a promising direction to improving the efficiency of autonomous...
arXiv:2601.18296v1 Announce Type: new Abstract: Temporal Knowledge Graph Question Answering (TKGQA) is inherently challenging, as it requires sophisticated reasoning over dynamic facts with multi-hop dependencies...
arXiv:2601.18298v1 Announce Type: new Abstract: Traditional cellular networks struggle with poor quality of service (QoS) for cell-edge users, while cell-free (CF) systems offer uniform QoS...
arXiv:2601.18300v1 Announce Type: new Abstract: Simulation techniques such as the finite element method are essential for designing electrical devices, but their computational cost can be...
arXiv:2601.18301v1 Announce Type: new Abstract: Range-view projection provides an efficient method for transforming 3D LiDAR point clouds into 2D range image representations, enabling effective processing...