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MOELIGA: a multi-objective evolutionary approach for feature selection with local improvement
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User Preference Modeling for Conversational LLM Agents: Weak Rewards from Retrieval-Augmented Interaction
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gUFO: A Gentle Foundational Ontology for Semantic Web Knowledge Graphs
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Before the Tool Call: Deterministic Pre-Action Authorization for Autonomous AI Agents
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Beyond Expression Similarity: Contrastive Learning Recovers Functional Gene Associations from Protein Interaction Structure
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Errors in AI-Assisted Retrieval of Medical Literature: A Comparative Study
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Alignment Whack-a-Mole : Finetuning Activates Verbatim Recall of Copyrighted Books in Large Language Models
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Elite Lanes: Evolutionary Generation of Realistic Small-Scale Road Networks
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Learning to Aggregate Zero-Shot LLM Agents for Corporate Disclosure Classification
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Hard labels sampled from sparse targets mislead rotation invariant algorithms
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Understanding Contextual Recall in Transformers: How Finetuning Enables In-Context Reasoning over Pretraining Knowledge
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GraPHFormer: A Multimodal Graph Persistent Homology Transformer for the Analysis of Neuroscience Morphologies
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DiscoUQ: Structured Disagreement Analysis for Uncertainty Quantification in LLM Agent Ensembles
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Detection of adversarial intent in Human-AI teams using LLMs
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From Causal Discovery to Dynamic Causal Inference in Neural Time Series
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Cyber Deception for Mission Surveillance via Hypergame-Theoretic Deep Reinforcement Learning
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LJ-Bench: Ontology-Based Benchmark for U.S. Crime
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Context Cartography: Toward Structured Governance of Contextual Space in Large Language Model Systems
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JUBAKU: An Adversarial Benchmark for Exposing Culturally Grounded Stereotypes in Japanese LLMs
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GHOST: Ground-projected Hypotheses from Observed Structure-from-Motion Trajectories
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Improving Diffusion Generalization with Weak-to-Strong Segmented Guidance
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RECLAIM: Cyclic Causal Discovery Amid Measurement Noise
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MKA: Memory-Keyed Attention for Efficient Long-Context Reasoning
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Neural collapse in the orthoplex regime
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RayMap3R: Inference-Time RayMap for Dynamic 3D Reconstruction
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Generating from Discrete Distributions Using Diffusions: Insights from Random Constraint Satisfaction Problems
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Position: Multi-Agent Algorithmic Care Systems Demand Contestability for Trustworthy AI
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Graph-based data-driven discovery of interpretable laws governing corona-induced noise and radio interference for high-voltage transmission lines
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Interpretable Operator Learning for Inverse Problems via Adaptive Spectral Filtering: Convergence and Discretization Invariance
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Bayesian Learning in Episodic Zero-Sum Games
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Towards Practical World Model-based Reinforcement Learning for Vision-Language-Action Models
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GaussianPile: A Unified Sparse Gaussian Splatting Framework for Slice-based Volumetric Reconstruction
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Beyond Token Eviction: Mixed-Dimension Budget Allocation for Efficient KV Cache Compression
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Reasoning Traces Shape Outputs but Models Won't Say So
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Causal Direct Preference Optimization for Distributionally Robust Generative Recommendation
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LassoFlexNet: Flexible Neural Architecture for Tabular Data
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Optimal low-rank stochastic gradient estimation for LLM training
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Seed1.8 Model Card: Towards Generalized Real-World Agency
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CFNN: Continued Fraction Neural Network
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A Modular LLM Framework for Explainable Price Outlier Detection
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AEGIS: From Clues to Verdicts -- Graph-Guided Deep Vulnerability Reasoning via Dialectics and Meta-Auditing
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Agentic AI and the next intelligence explosion
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Hear Both Sides: Efficient Multi-Agent Debate via Diversity-Aware Message Retention
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Weber's Law in Transformer Magnitude Representations: Efficient Coding, Representational Geometry, and Psychophysical Laws in Language Models
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ScaleEdit-12M: Scaling Open-Source Image Editing Data Generation via Multi-Agent Framework
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Diffusion Model for Manifold Data: Score Decomposition, Curvature, and Statistical Complexity
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A Multihead Continual Learning Framework for Fine-Grained Fashion Image Retrieval with Contrastive Learning and Exponential Moving Average Distillation
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From 50% to Mastery in 3 Days: A Low-Resource SOP for Localizing Graduate-Level AI Tutors via Shadow-RAG
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Modernizing Amdahl's Law: How AI Scaling Laws Shape Computer Architecture
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Exponential Family Discriminant Analysis: Generalizing LDA-Style Generative Classification to Non-Gaussian Models
