arXiv:2512.12109v2 Announce Type: replace-cross Abstract: Automated eligibility systems increasingly determine access to essential public benefits, but the explanations they generate often fail to reflect the legal rules that authorize those decisions. This thesis develops a legally grounded explainability framework that links system-generated decision justifications to the statutory constraints of CalFresh, California’s Supplemental Nutrition Assistance Program. […]
Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challenges
arXiv:2512.04770v2 Announce Type: replace-cross Abstract: Brain-body co-evolution enables animals to develop complex behaviors in their environments. Inspired by this biological synergy, embodied co-design (ECD) has emerged as a transformative paradigm for creating intelligent agents-from virtual creatures to physical robots-by jointly optimizing their morphologies and controllers rather than treating control in isolation. This integrated approach facilitates […]
Memo2496: Expert-Annotated Dataset and Dual-View Adaptive Framework for Music Emotion Recognition
arXiv:2512.13998v2 Announce Type: replace-cross Abstract: Music Emotion Recogniser (MER) research faces challenges due to limited high-quality annotated datasets and difficulties in addressing cross-track feature drift. This work presents two primary contributions to address these issues. Memo2496, a large-scale dataset, offers 2496 instrumental music tracks with continuous valence arousal labels, annotated by 30 certified music specialists. […]
Quantum Machine Learning for Cybersecurity: A Taxonomy and Future Directions
arXiv:2512.15286v1 Announce Type: cross Abstract: The increasing number of cyber threats and rapidly evolving tactics, as well as the high volume of data in recent years, have caused classical machine learning, rules, and signature-based defence strategies to fail, rendering them unable to keep up. An alternative, Quantum Machine Learning (QML), has recently emerged, making use […]
Graph Pattern-based Association Rules Evaluated Under No-repeated-anything Semantics in the Graph Transactional Setting
arXiv:2512.15308v1 Announce Type: cross Abstract: We introduce graph pattern-based association rules (GPARs) for directed labeled multigraphs such as RDF graphs. GPARs support both generative tasks, where a graph is extended, and evaluative tasks, where the plausibility of a graph is assessed. The framework goes beyond related formalisms such as graph functional dependencies, graph entity dependencies, […]
VLegal-Bench: Cognitively Grounded Benchmark for Vietnamese Legal Reasoning of Large Language Models
arXiv:2512.14554v2 Announce Type: replace-cross Abstract: The rapid advancement of large language models (LLMs) has enabled new possibilities for applying artificial intelligence within the legal domain. Nonetheless, the complexity, hierarchical organization, and frequent revisions of Vietnamese legislation pose considerable challenges for evaluating how well these models interpret and utilize legal knowledge. To address this gap, Vietnamese […]
Attention as Binding: A Vector-Symbolic Perspective on Transformer Reasoning
arXiv:2512.14709v1 Announce Type: new Abstract: Transformer-based language models display impressive reasoning-like behavior, yet remain brittle on tasks that require stable symbolic manipulation. This paper develops a unified perspective on these phenomena by interpreting self-attention and residual streams as implementing an approximate Vector Symbolic Architecture (VSA). In this view, queries and keys define role spaces, values […]
Prompt-Based Continual Compositional Zero-Shot Learning
arXiv:2512.09172v2 Announce Type: replace-cross Abstract: We tackle continual adaptation of vision-language models to new attributes, objects, and their compositions in Compositional Zero-Shot Learning (CZSL), while preventing forgetting of prior knowledge. Unlike classical continual learning where classes are disjoint, CCZSL is more complex as attributes and objects may reoccur across sessions while compositions remain unique. Built […]
Well Begun, Half Done: Reinforcement Learning with Prefix Optimization for LLM Reasoning
arXiv:2512.15274v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) significantly enhances the reasoning capability of Large Language Models (LLMs). Current RLVR approaches typically conduct training across all generated tokens, but neglect to explore which tokens (e.g., prefix tokens) actually contribute to reasoning. This uniform training strategy spends substantial effort on optimizing low-return tokens, […]
Modeling Plant Action Potentials under Photoperiod Stress via Hodgkin-Huxley Dynamics
arXiv:2512.15236v1 Announce Type: cross Abstract: Plants exhibit dynamic bioelectric properties that facilitate information transfer across tissues. This study investigates action potentials (APs) in Nicotiana tabacum recorded within a custom-designed growth chamber using a biosignal amplifier and environmental sensors. Consistent light- and dark-induced APs were observed during photoperiod transitions under controlled 12-hour artificial illumination cycles. To […]