arXiv:2601.20601v1 Announce Type: cross Abstract: Medical image classification is a core task in computer-aided diagnosis (CAD), playing a pivotal role in early disease detection, treatment planning, and patient prognosis assessment. In ophthalmic practice, fluorescein fundus angiography (FFA) and indocyanine green angiography (ICGA) provide hemodynamic and lesion-structural information that conventional fundus photography cannot capture. However, due […]
Benchmarking von ASR-Modellen im deutschen medizinischen Kontext: Eine Leistungsanalyse anhand von Anamnesegespr”achen
arXiv:2601.19945v1 Announce Type: cross Abstract: Automatic Speech Recognition (ASR) offers significant potential to reduce the workload of medical personnel, for example, through the automation of documentation tasks. While numerous benchmarks exist for the English language, specific evaluations for the German-speaking medical context are still lacking, particularly regarding the inclusion of dialects. In this article, we […]
Interpreting Emergent Extreme Events in Multi-Agent Systems
arXiv:2601.20538v1 Announce Type: cross Abstract: Large language model-powered multi-agent systems have emerged as powerful tools for simulating complex human-like systems. The interactions within these systems often lead to extreme events whose origins remain obscured by the black box of emergence. Interpreting these events is critical for system safety. This paper proposes the first framework for […]
Diffusion Generative Recommendation with Continuous Tokens
arXiv:2504.12007v4 Announce Type: replace-cross Abstract: Recent advances in generative artificial intelligence, particularly large language models (LLMs), have opened new opportunities for enhancing recommender systems (RecSys). Most existing LLM-based RecSys approaches operate in a discrete space, using vector-quantized tokenizers to align with the inherent discrete nature of language models. However, these quantization methods often result in […]
Bayesian dictionary learning estimation of cell membrane permeability from surface pH data
arXiv:2507.09651v2 Announce Type: replace-cross Abstract: Gas transport across cell membrane is a very important process in biochemistry which is essential for many crucial tasks, including cell respiration pH regulation in the cell. In the late 1990’s, the suggestion that gasses are transported via preferred gas channels embedded into the cell membrane challenged the century old […]
SysMoBench: Evaluating AI on Formally Modeling Complex Real-World Systems
arXiv:2509.23130v3 Announce Type: replace Abstract: Formal models are essential to specifying large, complex computer systems and verifying their correctness, but are notoriously expensive to write and maintain. Recent advances in generative AI show promise in generating certain forms of specifications. However, existing work mostly targets small code, not complete systems. It is unclear whether AI […]
A Scalable Inter-edge Correlation Modeling in CopulaGNN for Link Sign Prediction
arXiv:2601.19175v2 Announce Type: replace-cross Abstract: Link sign prediction on a signed graph is a task to determine whether the relationship represented by an edge is positive or negative. Since the presence of negative edges violates the graph homophily assumption that adjacent nodes are similar, regular graph methods have not been applicable without auxiliary structures to […]
$mathbbR^2k$ is Theoretically Large Enough for Embedding-based Top-$k$ Retrieval
arXiv:2601.20844v1 Announce Type: cross Abstract: This paper studies the minimal dimension required to embed subset memberships ($m$ elements and $mchoose k$ subsets of at most $k$ elements) into vector spaces, denoted as Minimal Embeddable Dimension (MED). The tight bounds of MED are derived theoretically and supported empirically for various notions of “distances” or “similarities,” including […]
Gradient Dynamics of Attention: How Cross-Entropy Sculpts Bayesian Manifolds
arXiv:2512.22473v3 Announce Type: replace-cross Abstract: Transformers empirically perform precise probabilistic reasoning in carefully constructed “Bayesian wind tunnels” and in large-scale language models, yet the mechanisms by which gradient-based learning creates the required internal geometry remain opaque. We provide a complete first-order analysis of how cross-entropy training reshapes attention scores and value vectors in a transformer […]
RacketVision: A Multiple Racket Sports Benchmark for Unified Ball and Racket Analysis
arXiv:2511.17045v3 Announce Type: replace-cross Abstract: We introduce RacketVision, a novel dataset and benchmark for advancing computer vision in sports analytics, covering table tennis, tennis, and badminton. The dataset is the first to provide large-scale, fine-grained annotations for racket pose alongside traditional ball positions, enabling research into complex human-object interactions. It is designed to tackle three […]
RxnBench: A Multimodal Benchmark for Evaluating Large Language Models on Chemical Reaction Understanding from Scientific Literature
arXiv:2512.23565v5 Announce Type: replace-cross Abstract: The integration of Multimodal Large Language Models (MLLMs) into chemistry promises to revolutionize scientific discovery, yet their ability to comprehend the dense, graphical language of reactions within authentic literature remains underexplored. Here, we introduce RxnBench, a multi-tiered benchmark designed to rigorously evaluate MLLMs on chemical reaction understanding from scientific PDFs. […]
Ranking-aware Reinforcement Learning for Ordinal Ranking
arXiv:2601.20585v1 Announce Type: cross Abstract: Ordinal regression and ranking are challenging due to inherent ordinal dependencies that conventional methods struggle to model. We propose Ranking-Aware Reinforcement Learning (RARL), a novel RL framework that explicitly learns these relationships. At its core, RARL features a unified objective that synergistically integrates regression and Learning-to-Rank (L2R), enabling mutual improvement […]