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arXiv:2509.11517v2 Announce Type: replace Abstract: BACKGROUND: Medical large language models (LLMs) have demonstrated remarkable performance in answering medical examinations. However, the extent to which this...
arXiv:2509.11754v2 Announce Type: replace Abstract: Foundational models of computation often abstract away physical hardware limitations. However, in extreme environments like In-Network Computing (INC), these limitations...
arXiv:2509.11787v3 Announce Type: replace Abstract: Static analysis tools are widely used to detect bugs, vulnerabilities, and code smells. Traditionally, developers must resolve these warnings manually....
arXiv:2509.11791v2 Announce Type: replace Abstract: This paper investigates how the performance of visual navigation policies trained in simulation compares to policies trained with real-world data....
arXiv:2509.14537v2 Announce Type: replace Abstract: Capturing professionals' decision-making in creative workflows (e.g., UI/UX) is essential for reflection, collaboration, and knowledge sharing, yet existing methods often...
arXiv:2509.18880v3 Announce Type: replace Abstract: Detecting AI-generated text is an increasing necessity to combat misuse of LLMs in education, business compliance, journalism, and social media,...
arXiv:2509.21073v2 Announce Type: replace Abstract: The field of general-purpose robotics has recently embraced powerful probabilistic diffusion-based models to learn the complex embodiment behaviours. However, existing...
arXiv:2509.21500v2 Announce Type: replace Abstract: Reinforcement fine-tuning (RFT) often suffers from reward over-optimization, where a policy model hacks the reward signals to achieve high scores...
arXiv:2509.21865v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) is a framework for grounding Large Language Models (LLMs) in external, up-to-date information. However, recent advancements in...
arXiv:2509.22548v2 Announce Type: replace Abstract: Vision-and-Language Navigation requires an embodied agent to navigate through unseen environments, guided by natural language instructions and a continuous video...
arXiv:2509.23253v3 Announce Type: replace Abstract: Spiking Neural Networks (SNNs) have garnered significant attention as a central paradigm in neuromorphic computing, owing to their energy efficiency...
arXiv:2509.23597v3 Announce Type: replace Abstract: Time series forecasting remains a critical challenge across numerous domains, yet the effectiveness of complex models often varies unpredictably across...
arXiv:2509.23744v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) promise enhanced reasoning by integrating diverse inputs such as text, vision, and audio. Yet cross-modal...
arXiv:2509.24072v4 Announce Type: replace Abstract: Large vision-language models (LVLMs) show strong performance across multimodal benchmarks but remain limited in structured reasoning and precise grounding. Recent...
arXiv:2509.25184v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in modern search and answer systems to synthesize multiple, sometimes conflicting, texts into...
arXiv:2509.25800v2 Announce Type: replace Abstract: Interventional causal discovery seeks to identify causal relations by leveraging distributional changes introduced by interventions, even in the presence of...
arXiv:2510.00024v2 Announce Type: replace Abstract: Large Language Models (LLMs) offer new opportunities to accelerate complex interdisciplinary research domains. Epidemic modeling, characterized by its complexity and...
arXiv:2510.00981v3 Announce Type: replace Abstract: Neural audio codecs are foundational to speech language models. It is expected to have a low frame rate and decoupled...
arXiv:2510.01988v5 Announce Type: replace Abstract: Antimicrobial peptide discovery is challenged by the astronomical size of peptide space and the relative scarcity of active peptides. Generative...
arXiv:2510.02823v4 Announce Type: replace Abstract: State Space Models (SSMs), developed to tackle long sequence modeling tasks efficiently, offer both parallelizable training and fast inference. At...
arXiv:2510.03255v2 Announce Type: replace Abstract: The scientific reasoning ability of large language models (LLMs) has recently attracted significant attention. Time series, as a fundamental modality...
arXiv:2510.04091v2 Announce Type: replace Abstract: Partial multi-label learning and complementary multi-label learning are two popular weakly supervised multi-label classification paradigms that aim to alleviate the...
arXiv:2510.05077v2 Announce Type: replace Abstract: With the rapid development of language models, the number of small language models (SLMs) has grown significantly. Although they do...
arXiv:2510.09167v2 Announce Type: replace Abstract: Recommender Systems (RS) are fundamental to modern online services. While most existing approaches optimize for short-term engagement, recent work has...