LatentWave: JEPA Pretraining for Wireless Foundation Models
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ReTreVal: Reasoning Tree with Validation and Cross-Problem Memory for Large Language Mode…
MARDoc: A Memory-Aware Refinement Agent Framework for Multimodal Long Document QA
CoT-Space: A Theoretical Framework for Internal Slow-Thinking via Reinforcement Learning
TempoVLA: Learning Speed-Controllable Vision-Language-Action Policies
Beyond Soft Masks: Hard-Perturbation Mixup Explainer for Robust GNN Explainability
CollabBench: Benchmarking and Unleashing Collaborative Ability of LLMs with Diverse Playe…
Learning Geometric Representations from Videos for Spatial Intelligent Multimodal Large L…
RREDCoT: Segment-Level Reward Redistribution for Reasoning Models
LLMCodec: Adapting Video Codecs for Efficient Weight Compression of Large Language Models
RiskFlow: Fast and Faithful Safety-Critical Traffic Scenario Generation
Agentic Monte Carlo: Simulating Reinforcement Learning for Black-Box Agents
AIS-Based Vessel Trajectory Prediction Using Memory-Augmented Neural Networks
LLM Self-Recognition: Steering and Retrieving Activation Signatures
Surrogate Neural Architecture Codesign Package (SNAC-Pack)
Gradient descent at the Edge of Stability: free energy model and kinetic description of t…
The Invisible Hand of Physics: When Video Diffusion Models Know More Than They Show
Towards an Inferentialist Account of Information Through Proof-theoretic Semantics
Where Should Knowledge Enter? A Layered Framework for Knowledge Infusion in Multimodal It…
Query-efficient model evaluation using cached responses
Fix the Mind, Not the Move: Interpretable AI Assistance via Knowledge-Gap Localization
Learning to Theorize the World from Observation
Evaluation of LLMs for Mathematical Formalization in Lean
Humans' ALMANAC: A Human Collaboration Dataset of Action-Level Mental Model Annotations f…
Where's the Structure? A Systematic Literature Review of Empirical Research on Human-AI C…
AdaMEM: Test-Time Adaptive Memory for Language Agents
Reward Learning through Ranking Mean Squared Error
DiG-Plan: Mitigating Early Commitment for Tool-Graph Planning via Diffusion Guidance
When AI Says It Feels
Benchmark Everything Everywhere All at Once