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Learning and Reusing Policy Decompositions for Hierarchical Generalized Planning with LLM Agents
Multi-Objective Constraint Inference using Inverse reinforcement learning
Self-Programmed Execution for Language-Model Agents
Mitigating Cognitive Bias in RLHF by Altering Rationality
Beyond the Black Box: Interpretability of Agentic AI Tool Use
How Well Do LLMs Perform on the Simplest Long-Chain Reasoning Tasks: An Empirical Study on the Equivalence Class Problem
Agentick: A Unified Benchmark for General Sequential Decision-Making Agents
AGWM: Affordance-Grounded World Models for Environments with Compositional Prerequisites
Extracting Search Trees from LLM Reasoning Traces Reveals Myopic Planning
Randomness is sometimes necessary for coordination
Uneven Evolution of Cognition Across Generations of Generative AI Models
Towards Security-Auditable LLM Agents: A Unified Graph Representation
When Does Critique Improve AI-Assisted Theoretical Physics? SCALAR: Structured Critic--Actor Loop for Agentic Reasoning
Weblica: Scalable and Reproducible Training Environments for Visual Web Agents
When Does a Language Model Commit? A Finite-Answer Theory of Pre-Verbalization Commitment
From Storage to Experience: A Survey on the Evolution of LLM Agent Memory Mechanisms
CASCADE: Case-Based Continual Adaptation for Large Language Models During Deployment
Hidden Coalitions in Multi-Agent AI: A Spectral Diagnostic from Internal Representations
State Representation and Termination for Recursive Reasoning Systems
Fast and Effective Redistricting Optimization via Composite-Move Tabu Search
More Thinking, More Bias: Length-Driven Position Bias in Reasoning Models
GraphDC: A Divide-and-Conquer Multi-Agent System for Scalable Graph Algorithm Reasoning
Continual Knowledge Updating in LLM Systems: Learning Through Multi-Timescale Memory Dynamics
Predictive and Prescriptive AI toward Optimizing Wildfire Suppression
Structured Progressive Knowledge Activation for LLM-Driven Neural Architecture Search
AniMatrix: An Anime Video Generation Model that Thinks in Art, Not Physics
HeadQ: Model-Visible Distortion and Score-Space Correction for KV-Cache Quantization
MEMSAD: Gradient-Coupled Anomaly Detection for Memory Poisoning in Retrieval-Augmented Agents
When Agents Handle Secrets: A Survey of Confidential Computing for Agentic AI
Probe-Geometry Alignment: Erasing the Cross-Sequence Memorization Signature Below Chance
AgriKD: Cross-Architecture Knowledge Distillation for Efficient Leaf Disease Classification
Are we Doomed to an AI Race? Why Self-Interest Could Drive Countries Towards a Moratorium on Superintelligence
Separation Assurance between Heterogeneous Fleets of Small Unmanned Aerial Systems via Multi-Agent Reinforcement Learning
H-Probes: Extracting Hierarchical Structures From Latent Representations of Language Models
InvEvolve: Evolving White-Box Inventory Policies via Large Language Models with Performance Guarantees
Caracal: Causal Architecture via Spectral Mixing
RSAT: Structured Attribution Makes Small Language Models Faithful Table Reasoners
ANCORA: Learning to Question via Manifold-Anchored Self-Play for Verifiable Reasoning
How Fast Should a Model Commit to Supervision? Training Reasoning Models on the Tsallis Loss Continuum
asRoBallet: Closing the Sim2Real Gap via Friction-Aware Reinforcement Learning for Underactuated Spherical Dynamics
Mochi: Aligning Pre-training and Inference for Efficient Graph Foundation Models via Meta-Learning
Enhancing Science Classroom Discourse Analysis through Joint Multi-Task Learning for Reasoning-Component Classification
Enhancing Speaker Verification with Whispered Speech via Post-Processing
Information Aggregation with AI Agents
Low-Rank Adaptation for Critic Learning in Off-Policy Reinforcement Learning
Handling and Interpreting Missing Modalities in Patient Clinical Trajectories via Autoregressive Sequence Modeling
Latent Abstraction for Retrieval-Augmented Generation
Reward Score Matching: Unifying Reward-based Fine-tuning for Flow and Diffusion Models
SSMamba: A Self-Supervised Hybrid State Space Model for Pathological Image Classification
DeEscalWild: A Real-World Benchmark for Automated De-Escalation Training with SLMs
Frequency-Enhanced Diffusion Models: Curriculum-Guided Semantic Alignment for Zero-Shot Skeleton Action Recognition
MAT-Cell: A Multi-Agent Tree-Structured Reasoning Framework for Batch-Level Single-Cell Annotation
StableTTA: Improving Vision Model Performance by Training-free Test-Time Adaptation Methods
Screening Is Enough
Bringing Up a Bilingual BabyLM: Investigating Multilingual Language Acquisition Using Small-Scale Models
Spectral Edge Dynamics: An Analytical-Empirical Study of Phase Transitions in Neural Network Training
Prediction-Based Markov Violation Scores for Detecting Non-Markovian Observations in Reinforcement Learning
P^2O: Joint Policy and Prompt Optimization
Structural Sensitivity in Compressed Transformers: Relative Error Propagation and Layer Removal
Epistemic Observability in Language Models
Adaptive Greedy Frame Selection for Long Video Understanding
Spectral Alignment in Forward-Backward Representations via Temporal Abstraction
Discovering What You Can Control: Interventional Boundary Discovery for Reinforcement Learning
Alternating Reinforcement Learning with Contextual Rubric Rewards: Beyond the Scalarization Strategy
From Documents to Spans: Scalable Supervision for Evidence-Based ICD Coding with LLMs
ChArtist: Generating Pictorial Charts with Unified Spatial and Subject Control
MetaKE: Meta-Learning for Knowledge Editing Toward a Better Accuracy-Editability Trade-off
Unsupervised Anomaly Detection in Wearable Foot Sensor Data: A Baseline Feasibility Study Towards Diabetic Foot Ulcer Prevention
Quantifying Hallucinations in Language Language Models on Medical Textbooks
DC-DiT: Adaptive Compute and Elastic Inference for Visual Generation via Dynamic Chunking
DARK: Diagonal-Anchored Repulsive Knowledge Distillation for Vision-Language Models under Extreme Compression
PulseLM: A Foundation Dataset and Benchmark for PPG-Text Learning
Path Dependence under Adaptive AI Delegation
A Detection-Gated Pipeline for Robust Glottal Area Waveform Extraction and Clinical Pathology Assessment
PEPA: a Persistently Autonomous Embodied Agent with Personalities
AI Agents Alone Are Not (Yet) Sufficient for Social Simulation
Same Words, Different Judgments: How Preferences Vary Across Modalities
CAMEL: Confidence-Gated Reflection for Reward Modeling
Decentralized Attention Fails Centralized Signals: Rethinking Transformers for Medical Time Series
Perceptive Humanoid Parkour: Chaining Dynamic Human Skills via Motion Matching
Molecular Design beyond Training Data with Novel Extended Objective Functionals of Generative AI Models Driven by Quantum Annealing Computer
On the Rate-Distortion-Complexity Tradeoff for Semantic Communication
Visual Para-Thinker: Divide-and-Conquer Reasoning for Visual Comprehension
Risk Horizons: Structured Hypothesis Spaces for Longitudinal Clinical Prediction
Multimodal Fact-Level Attribution for Verifiable Reasoning
AceGRPO: Adaptive Curriculum Enhanced Group Relative Policy Optimization for Autonomous Machine Learning Engineering
Action-to-Action Flow Matching
A Theoretical Analysis of Test-Driven Code Generation
Parity, Sensitivity, and Transformers
It's Not a Lottery, It's a Race: Understanding How Gradient Descent Adapts the Network's Capacity to the Task
PixelGen: Improving Pixel Diffusion with Perceptual Supervision
AROpt: An Optimization Method for Autoregressive Time Series Forecasting
DOGMA: Weaving Structural Information into Data-centric Single-cell Transcriptomics Analysis
Toward Scalable Audio Description Quality Control: A Workflow for Evaluating Human and VLM Raters
SMI: Statistical Membership Inference for Reliable Unlearned Model Auditing
The Illusion of Forgetting: Attack Unlearned Diffusion via Initial Latent Variable Optimization
How Hyper-Datafication Impacts the Sustainability Costs in Frontier AI
DialectLLM: A Dialect-Aware Dialog[ue] Generation Framework Beyond Standard American English
Keep Rehearsing and Refining: Lifelong Learning Vehicle Routing under Continually Drifting Tasks
Leviathan: Decoupling Input and Output Representations in Language Models
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