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arXiv:2601.21941v1 Announce Type: new Abstract: Medical multimodal representation learning aims to integrate heterogeneous data into unified patient representations to support clinical outcome prediction. However, real-world...
arXiv:2601.21943v1 Announce Type: new Abstract: Diffusion generative models synthesize samples by discretizing reverse-time dynamics driven by a learned score (or denoiser). Existing convergence analyses of...
arXiv:2601.21944v1 Announce Type: new Abstract: The widespread adoption of Vision-Language Models (VLMs) across fields has amplified concerns about model interpretability. Distressingly, these models are often...
arXiv:2601.21945v1 Announce Type: new Abstract: The rapid rise of artificial intelligence has led to an unsustainable growth in energy consumption. This has motivated progress in...
arXiv:2601.21947v1 Announce Type: new Abstract: Prevalent retrieval-based tool-use pipelines struggle with a dual semantic challenge: their retrievers often employ encoders that fail to capture complex...
arXiv:2601.21948v1 Announce Type: new Abstract: Neural visual decoding is a central problem in brain computer interface research, aiming to reconstruct human visual perception and to...
arXiv:2601.21950v1 Announce Type: new Abstract: Medical multimodal learning faces significant challenges with missing modalities prevalent in clinical practice. Existing approaches assume equal contribution of modality...
arXiv:2601.21955v1 Announce Type: new Abstract: The increasing availability of unstructured clinical narratives in electronic health records (EHRs) has created new opportunities for automated disease characterization,...
arXiv:2601.21956v1 Announce Type: new Abstract: Data-based optimization (DBO) offers a promising approach for efficiently optimizing shape for better aerodynamic performance by leveraging a pretrained surrogate...
arXiv:2601.21957v1 Announce Type: new Abstract: We introduce PaddleOCR-VL-1.5, an upgraded model achieving a new state-of-the-art (SOTA) accuracy of 94.5% on OmniDocBench v1.5. To rigorously evaluate...
arXiv:2601.21961v1 Announce Type: new Abstract: Web agents have demonstrated strong performance on a wide range of web-based tasks. However, existing research on the effect of...
arXiv:2601.21963v1 Announce Type: new Abstract: Generative AI and misinformation research has evolved since our 2024 survey. This paper presents an updated perspective, transitioning from literature...
arXiv:2601.21964v1 Announce Type: new Abstract: Drug discovery can be viewed as a combinatorial search over an immense chemical space, motivating the development of deep generative...
arXiv:2601.21965v1 Announce Type: new Abstract: Accurately monitoring cognitive load in real time is critical for Brain-Computer Interfaces (BCIs) that adapt to user engagement and support...
arXiv:2601.21966v1 Announce Type: new Abstract: Cyber-Physical Systems (CPSs) rely on distributed embedded devices that often must communicate securely over buses. Ensuring message integrity and authenticity...
arXiv:2601.21967v1 Announce Type: new Abstract: AI research has traditionally prioritised algorithmic performance, such as optimising accuracy in machine learning or runtime in automated planning. The...
arXiv:2601.21968v1 Announce Type: new Abstract: Knowledge distillation offers a promising path to transfer reasoning capabilities from large teacher models to efficient student models; however, existing...
arXiv:2601.21969v1 Announce Type: new Abstract: Large Language Models (LLMs) often hallucinate, generating content inconsistent with the input. Retrieval-Augmented Generation (RAG) and Reinforcement Learning with Human...
arXiv:2601.21971v1 Announce Type: new Abstract: Imitation learning has achieved remarkable success in robotic manipulation, yet its application to surgical robotics remains challenging due to data...
arXiv:2601.21972v1 Announce Type: new Abstract: Recent work has explored optimizing LLM collaboration through Multi-Agent Reinforcement Learning (MARL). However, most MARL fine-tuning approaches rely on predefined...
arXiv:2601.21975v1 Announce Type: new Abstract: Recent work identifies a stated-revealed (SvR) preference gap in language models (LMs): a mismatch between the values models endorse and...
arXiv:2601.21976v1 Announce Type: new Abstract: Foldable robots have been an active area of robotics research due to their high volume-to-mass ratio, easy packability, and shape...
arXiv:2601.21977v1 Announce Type: new Abstract: Traditional architectural simulations (e.g. Computational Fluid Dynamics, evacuation, structural analysis) model elements as deterministic physics-based "particles" rather than cognitive "agents"....
arXiv:2601.21978v1 Announce Type: new Abstract: Temporal knowledge graph reasoning (TKGR) aims to predict future events by inferring missing entities with dynamic knowledge structures. Existing LLM-based...