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Final Report for the Workshop on Robotics & AI in Medicine
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GMT: Goal-Conditioned Multimodal Transformer for 6-DOF Object Trajectory Synthesis in 3D Scenes
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LoST: Level of Semantics Tokenization for 3D Shapes
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The Unreasonable Effectiveness of Text Embedding Interpolation for Continuous Image Steering
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AgentFactory: A Self-Evolving Framework Through Executable Subagent Accumulation and Reuse
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EchoGen: Cycle-Consistent Learning for Unified Layout-Image Generation and Understanding
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Loc3R-VLM: Language-based Localization and 3D Reasoning with Vision-Language Models
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Universal Skeleton Understanding via Differentiable Rendering and MLLMs
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Unified Spatio-Temporal Token Scoring for Efficient Video VLMs
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Towards sample-optimal learning of bosonic Gaussian quantum states
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Learning-Augmented Algorithms for $k$-median via Online Learning
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How LLMs Distort Our Written Language
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Efficient Dense Crowd Trajectory Prediction Via Dynamic Clustering
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ResNets of All Shapes and Sizes: Convergence of Training Dynamics in the Large-scale Limit
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Modeling the human lexicon under temperature variations: linguistic factors, diversity and typicality in LLM word associations
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GRAFITE: Generative Regression Analysis Framework for Issue Tracking and Evaluation
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Conflict-Free Policy Languages for Probabilistic ML Predicates: A Framework and Case Study with the Semantic Router DSL
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VLM-AutoDrive: Post-Training Vision-Language Models for Safety-Critical Autonomous Driving Events
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CWoMP: Morpheme Representation Learning for Interlinear Glossing
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TeachingCoach: A Fine-Tuned Scaffolding Chatbot for Instructional Guidance to Instructors
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Starting Off on the Wrong Foot: Pitfalls in Data Preparation
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MicroVision: An Open Dataset and Benchmark Models for Detecting Vulnerable Road Users and Micromobility Vehicles
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Goedel-Code-Prover: Hierarchical Proof Search for Open State-of-the-Art Code Verification
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Retrieval-Augmented LLMs for Security Incident Analysis
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Access Controlled Website Interaction for Agentic AI with Delegated Critical Tasks
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A Computationally Efficient Learning of Artificial Intelligence System Reliability Considering Error Propagation
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R2-Dreamer: Redundancy-Reduced World Models without Decoders or Augmentation
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How Psychological Learning Paradigms Shaped and Constrained Artificial Intelligence
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Tackling the Sign Problem in the Doped Hubbard Model with Normalizing Flows
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Semantic Segmentation and Depth Estimation for Real-Time Lunar Surface Mapping Using 3D Gaussian Splatting
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A Hybrid Conditional Diffusion-DeepONet Framework for High-Fidelity Stress Prediction in Hyperelastic Materials
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PAI: Fast, Accurate, and Full Benchmark Performance Projection with AI
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Toward Reliable, Safe, and Secure LLMs for Scientific Applications
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FalconBC: Flow matching for Amortized inference of Latent-CONditioned physiologic Boundary Conditions
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Gradient-Informed Temporal Sampling Improves Rollout Accuracy in PDE Surrogate Training
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Impact of automatic speech recognition quality on Alzheimer's disease detection from spontaneous speech: a reproducible benchmark study with lexical modeling and statistical validation
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AGRI-Fidelity: Evaluating the Reliability of Listenable Explanations for Poultry Disease Detection
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Computation-Utility-Privacy Tradeoffs in Bayesian Estimation
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MolRGen: A Training and Evaluation Setting for De Novo Molecular Generation with Reasonning Models
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Discovering What You Can Control: Interventional Boundary Discovery for Reinforcement Learning
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Sharpness-Aware Minimization in Logit Space Efficiently Enhances Direct Preference Optimization
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LRConv-NeRV: Low Rank Convolution for Efficient Neural Video Compression
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Enactor: From Traffic Simulators to Surrogate World Models
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Retrieval-Augmented LLM Agents: Learning to Learn from Experience
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EDM-ARS: A Domain-Specific Multi-Agent System for Automated Educational Data Mining Research
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Detection Is Cheap, Routing Is Learned: Why Refusal-Based Alignment Evaluation Fails
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On Additive Gaussian Processes for Wind Farm Power Prediction
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CycleCap: Improving VLMs Captioning Performance via Self-Supervised Cycle Consistency Fine-Tuning
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Offload or Overload: A Platform Measurement Study of Mobile Robotic Manipulation Workloads
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CORE: Robust Out-of-Distribution Detection via Confidence and Orthogonal Residual ScoringSeoul National University
