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cs.AI updates on arXiv.org

GIANTS: Generative Insight Anticipation from Scientific Literature Should We be Pedantic About Reasoning Errors in Machine Translation? Computational Implementation of a Model of Category-Theoretic Metaphor Comprehension CoSToM:Causal-oriented Steering for Intrinsic Theory-of-Mind Alignment in Large Language Models ASPIRin: Action Space Projection for Interactivity-Optimized Reinforcement Learning in Full-Duplex Speech Language Models CircuitSynth: Reliable Synthetic Data Generation Think in Sentences: Explicit Sentence Boundaries Enhance Language Model's Capabilities CodaRAG: Connecting the Dots with Associativity Inspired by Complementary Learning From Query to Counsel: Structured Reasoning with a Multi-Agent Framework and Dataset for Legal Consultation ReFEree: Reference-Free and Fine-Grained Method for Evaluating Factual Consistency in Real-World Code Summarization LLMs Should Incorporate Explicit Mechanisms for Human Empathy Early Decisions Matter: Proximity Bias and Initial Trajectory Shaping in Non-Autoregressive Diffusion Language Models Bridging Linguistic Gaps: Cross-Lingual Mapping in Pre-Training and Dataset for Enhanced Multilingual LLM Performance Computational Lesions in Multilingual Language Models Separate Shared and Language-specific Brain Alignment Efficient Process Reward Modeling via Contrastive Mutual Information Learning and Enforcing Context-Sensitive Control for LLMs Too Nice to Tell the Truth: Quantifying Agreeableness-Driven Sycophancy in Role-Playing Language Models Deep-Reporter: Deep Research for Grounded Multimodal Long-Form Generation Generating Multiple-Choice Knowledge Questions with Interpretable Difficulty Estimation using Knowledge Graphs and Large Language Models Do BERT Embeddings Encode Narrative Dimensions? A Token-Level Probing Analysis of Time, Space, Causality, and Character in Fiction TInR: Exploring Tool-Internalized Reasoning in Large Language Models Advancing Polish Language Modeling through Tokenizer Optimization in the Bielik v3 7B and 11B Series AOP-Smart: A RAG-Enhanced Large Language Model Framework for Adverse Outcome Pathway Analysis Mem$^2$Evolve: Towards Self-Evolving Agents via Co-Evolutionary Capability Expansion and Experience Distillation Uncertainty-Aware Web-Conditioned Scientific Fact-Checking A Systematic Analysis of the Impact of Persona Steering on LLM Capabilities When Verification Fails: How Compositionally Infeasible Claims Escape Rejection When Valid Signals Fail: Regime Boundaries Between LLM Features and RL Trading Policies Shared Emotion Geometry Across Small Language Models: A Cross-Architecture Study of Representation, Behavior, and Methodological Confounds Efficient Training for Cross-lingual Speech Language Models CocoaBench: Evaluating Unified Digital Agents in the Wild MathAgent: Adversarial Evolution of Constraint Graphs for Mathematical Reasoning Data Synthesis Exploring Knowledge Conflicts for Faithful LLM Reasoning: Benchmark and Method Do LLMs Know Tool Irrelevance? 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Evaluating Escalation Behavior in Automation with Language Models Kill-Chain Canaries: Stage-Level Tracking of Prompt Injection Across Attack Surfaces and Model Safety Tiers Multivariate Time Series Anomaly Detection via Dual-Branch Reconstruction and Autoregressive Flow-based Residual Density Estimation On the Spectral Geometry of Cross-Modal Representations: A Functional Map Diagnostic for Multimodal Alignment Structured Exploration and Exploitation of Label Functions for Automated Data Annotation MolPaQ: Modular Quantum-Classical Patch Learning for Interpretable Molecular Generation QuanBench+: A Unified Multi-Framework Benchmark for LLM-Based Quantum Code Generation Generating High Quality Synthetic Data for Dutch Medical Conversations Explainability and Certification of AI-Generated Educational Assessments LLM Nepotism in Organizational Governance Re-Mask and Redirect: Exploiting Denoising Irreversibility in Diffusion Language Models Unifying Ontology Construction and Semantic Alignment for Deterministic Enterprise Reasoning at Scale CID-TKG: Collaborative Historical Invariance and Evolutionary Dynamics Learning for Temporal Knowledge Graph Reasoning DeepReviewer 2.0: A Traceable Agentic System for Auditable Scientific Peer Review Reinforcement-aware Knowledge Distillation for LLM Reasoning Generative UI: LLMs are Effective UI Generators ACE-TA: An Agentic Teaching Assistant for Grounded Q&A, Quiz Generation, and Code Tutoring SubQuad: Near-Quadratic-Free Structure Inference with Distribution-Balanced Objectives in Adaptive Receptor framework LETGAMES: An LLM-Powered Gamified Approach to Cognitive Training for Patients with Cognitive Impairment A Horizon-Aware Decision-Support Framework for Demand Forecasting Model Selection in Resilient Production Planning Seven simple steps for log analysis in AI systems H-AdminSim: A Multi-Agent Simulator for Realistic Hospital Administrative Workflows with FHIR Integration LABBench2: An Improved Benchmark for AI Systems Performing Biology Research MCERF: Advancing Multimodal LLM Evaluation of Engineering Documentation with Enhanced Retrieval AgencyBench: Benchmarking the Frontiers of Autonomous Agents in 1M-Token Real-World Contexts Reasoning Models Will Sometimes Lie About Their Reasoning Multi-agent Adaptive Mechanism Design Relational Visual Similarity From Navigation to Refinement: Revealing the Two-Stage Nature of Flow-based Diffusion Models through Oracle Velocity On-the-Fly Adaptation to Quantization: Configuration-Aware LoRA for Efficient Fine-Tuning of Quantized LLMs STCast: Adaptive Boundary Alignment for Global and Regional Weather Forecasting HCAST: Human-Calibrated Autonomy Software Tasks OmniPrism: Learning Disentangled Visual Concept for Image Generation
Active Inference with a Self-Prior in the Mirror-Mark Task
Dongmin Kim, Hoshinori Kanazawa, Yasuo Kuniyoshi · 2026-04-02 · via cs.AI updates on arXiv.org

The mirror self-recognition test evaluates whether a subject touches a mark on its own body that is visible only in a mirror, and is widely used as an indicator of self-awareness. In this study, we present a computational model in which this behavior emerges spontaneously through a single mechanism, the self-prior, without any external reward. The self-prior, implemented with a Transformer, learns the density of familiar multisensory experiences; when a novel mark appears, the discrepancy from this learned distribution drives mark-directed behavior through active inference. A simulated infant, relying solely on vision and proprioception without tactile input, discovered a sticker placed on its own face in the mirror and removed it in approximately 70% of cases without any explicit instruction. Expected free energy decreased significantly after sticker removal, confirming that the self-prior operates as an internal criterion for distinguishing self from non-self. Cross-modal sampling further demonstrated that the self-prior captures visual--proprioceptive associations, functioning as a probabilistic body schema. These results provide a concise computational account of the key behavior observed in the mirror test and suggest that the free energy principle can serve as a unifying hypothesis for investigating the developmental origins of self-awareness. Code is available at: https://github.com/kim135797531/self-prior-mirror