arXiv:2509.19122v1 Announce Type: cross Abstract: The study on architecture and parameter characteristics remains the hot topic in the research of large language models. In this paper we concern with the characteristics of weight which are used to analyze the correlations…
arXiv:2509.18221v1 Announce Type: new Abstract: With the rising global burden of chronic diseases and the multimodal and heterogeneous clinical data (medical imaging, free-text recordings, wearable sensor streams, etc.), there is an urgent need for a unified multimodal AI framework that…
arXiv:2509.18953v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as promising solutions for robotic manipulation, yet their robustness to real-world physical variations remains critically underexplored. To bridge this gap, we propose Eva-VLA, the first unified framework that systematically evaluates…
arXiv:2509.18218v1 Announce Type: new Abstract: We posit that persisting and transforming similarity relations form the structural basis of any comprehensible dynamic system. This paper introduces Similarity Field Theory, a mathematical framework that formalizes the principles governing similarity values among entities…
arXiv:2509.16198v2 Announce Type: replace-cross Abstract: Large language models excel at function- and file-level code generation, yet generating complete repositories from scratch remains a fundamental challenge. This process demands coherent and reliable planning across proposal- and implementation-level stages, while natural language,…
arXiv:2509.18216v1 Announce Type: new Abstract: As AI foundation models grow in capability, a deeper question emerges: What shapes their internal cognitive identity — beyond fluency and output? Benchmarks measure behavior, but the soul of a model resides in its latent…
arXiv:2506.09532v2 Announce Type: replace-cross Abstract: We present Athena-PRM, a multimodal process reward model (PRM) designed to evaluate the reward score for each step in solving complex reasoning problems. Developing high-performance PRMs typically demands significant time and financial investment, primarily due…
arXiv:2509.18215v1 Announce Type: new Abstract: This paper presents a formal approach to explaining change of inference in Quantitative Bipolar Argumentation Frameworks (QBAFs). When drawing conclusions from a QBAF and updating the QBAF to then again draw conclusions (and so on),…
arXiv:2503.00046v2 Announce Type: replace-cross Abstract: Evaluating creativity is challenging, even for humans, not only because of its subjectivity but also because it involves complex cognitive processes. Inspired by work in marketing, we attempt to break down visual advertisement creativity into…
arXiv:2509.18132v1 Announce Type: new Abstract: Uncertainty is a fundamental challenge in medical practice, but current medical AI systems fail to explicitly quantify or communicate uncertainty in a way that aligns with clinical reasoning. Existing XAI works focus on interpreting model…
