Search: “models”

Retrieval-Augmented Tutoring for Algorithm Tracing and Problem-Solving in AI Education

arXiv:2605.12988v1 Announce Type: new Abstract: Students learning algorithms often need support as they interpret traces, debug reasoning errors, and apply procedures across unfamiliar problem instanc

tutorialsarxiv-cs-ai

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Revisiting DAgger in the Era of LLM-Agents

DGX agent

arXiv:2605.12913v1 Announce Type: new Abstract: Long-horizon LM agents learn from multi-turn interaction, where a single early mistake can alter the subsequent state distribution and derail the whole

safetyarxiv-cs-lg

14 May 2026

RoboEvolve: Co-Evolving Planner-Simulator for Robotic Manipulation with Limited Data

arXiv:2605.13775v1 Announce Type: cross Abstract: The scalability of robotic manipulation is fundamentally bottlenecked by the scarcity of task-aligned physical interaction data. While vision-language

safetyarxiv-cs-cv

Robust Sequential Experimental Design for A/B Testing

arXiv:2605.12899v1 Announce Type: cross Abstract: Experimental design has emerged as a powerful approach for improving the sample efficiency of A/B testing, yet existing designs rely critically on cor

The Bayesian Origin of the Probability Weighting Function in Human Representation of Probabilities

arXiv:2510.04698v3 Announce Type: replace-cross Abstract: Humans systematically misrepresent probability in a stereotyped inverse-S pattern. It has been documented for decades, but its origin remains

researcharxiv-cs-ai

Tight Sample Complexity Bounds for Entropic Best Policy Identification

arXiv:2605.13717v1 Announce Type: new Abstract: We study best-policy identification for finite-horizon risk-sensitive reinforcement learning under the entropic risk measure. Recent work established a

Twincher: Bijective Representation Learning for Robust Inversion of Continuous Systems

arXiv:2605.13470v1 Announce Type: new Abstract: Recent advances in AI have been primarily driven by large-scale neural architectures that excel at function approximation, rather than by tailored induc

tutorialsarxiv-cs-lg

VoxCor: Training-Free Volumetric Features for Multimodal Voxel Correspondence

arXiv:2605.13798v1 Announce Type: new Abstract: Cross-modal 3D medical image analysis requires voxelwise representations that remain anatomically consistent across imaging contrasts, scanners, and acq

What Happens Before Decoding? Prefill Determines GUI Grounding in VLMs

arXiv:2605.12549v1 Announce Type: new Abstract: Existing training-free approaches for GUI grounding often rely on multiple inference runs, such as iterative cropping or candidate aggregation, to ident

When to Act, Ask, or Learn: Uncertainty-Aware Policy Steering

arXiv:2602.22474v2 Announce Type: replace-cross Abstract: Policy steering is an emerging way to adapt robot behaviors at deployment-time: a learned verifier analyzes low-level action samples proposed

WildPose: A Unified Framework for Robust Pose Estimation in the Wild

arXiv:2605.12774v1 Announce Type: new Abstract: Estimating camera pose in dynamic environments is a critical challenge, as most visual SLAM and SfM methods assume static scenes. While recent dynamic-a

ZeD-MAP: Bundle Adjustment Guided Zero-Shot Depth Maps for Real-Time Aerial Imaging

arXiv:2604.04667v2 Announce Type: replace Abstract: Real-time depth reconstruction from ultra-high-resolution UAV imagery is essential for time-critical geospatial tasks such as disaster response, yet

Anti-Self-Distillation for Reasoning RL via Pointwise Mutual Information

arXiv:2605.11609v1 Announce Type: cross Abstract: On-policy self-distillation, where a student is pulled toward a copy of itself conditioned on privileged context (e.g., a verified solution or feedbac

safetyarxiv-cs-cl

Causal Algorithmic Recourse: Foundations and Methods

arXiv:2605.11373v1 Announce Type: cross Abstract: The trustworthiness of AI decision-making systems is increasingly important. A key feature of such systems is the ability to provide recommendations f

Certified Gradient-Based Contact-Rich Manipulation via Smoothing-Error Reachable Tubes

arXiv:2602.09368v2 Announce Type: replace Abstract: Gradient-based methods can efficiently optimize controllers by leveraging differentiable simulation and physical priors. However, contact-rich manip

safetyarxiv-cs-ro

Hardware

ChunkFlow: Communication-Aware Chunked Prefetching for Layerwise Offloading in Distributed Diffusion Transformer Inference

arXiv:2605.11335v1 Announce Type: cross Abstract: Layerwise offloading reduces the GPU memory footprint of large diffusion transformer (DiT) inference by prefetching upcoming layers from host memory,

hardwarearxiv-cs-lg

Compositional Neural Operators for Multi-Dimensional Fluid Dynamics

arXiv:2605.11691v1 Announce Type: new Abstract: Partial differential equations (PDEs) govern diverse physical phenomena, yet high-fidelity numerical solutions are computationally expensive and Machine

researcharxiv-cs-lg

Continuous Discovery of Vulnerabilities in LLM Serving Systems with Fuzzing

arXiv:2605.11202v1 Announce Type: cross Abstract: LLM inference and serving systems have become security-critical infrastructure; however, many of their most concerning failures arise from the serving

Controllable User Simulation

arXiv:2605.11519v1 Announce Type: cross Abstract: Using offline datasets to evaluate conversational agents often fails to cover rare scenarios or to support testing new policies. This has motivated th

safetyarxiv-cs-cl

Deep Minds and Shallow Probes

arXiv:2605.11448v1 Announce Type: new Abstract: Neural representations are not unique objects. Even when two systems realize the same downstream computation, their hidden coordinates may differ by rep

Agents

Deep Reasoning in General Purpose Agents via Structured Meta-Cognition

arXiv:2605.11388v1 Announce Type: new Abstract: Humans intuitively solve complex problems by flexibly shifting among reasoning modes: they plan, execute, revise intermediate goals, resolve ambiguity t

agentsarxiv-cs-cl

Delay-Empowered Causal Hierarchical Reinforcement Learning

arXiv:2605.12261v1 Announce Type: new Abstract: Many real-world tasks involve delayed effects, where the outcomes of actions emerge after varying time lags. Existing delay-aware reinforcement learning

Demystifying When Pruning Works via Representation Hierarchies

arXiv:2603.24652v3 Announce Type: replace Abstract: Network pruning, which removes less important parameters or architectures, is often expected to improve efficiency while preserving performance. How

researcharxiv-cs-cl

DiffSegLung: Diffusion Radiomic Distillation for Unsupervised Lung Pathology Segmentation

arXiv:2605.11758v1 Announce Type: cross Abstract: Unsupervised segmentation of pulmonary pathologies in CT remains an open challenge due to the absence of annotated multi pathology cohorts and the fai

Elastic Attention Cores for Scalable Vision Transformers

arXiv:2605.12491v1 Announce Type: new Abstract: Vision Transformers (ViTs) achieve strong data-driven scaling by leveraging all-to-all self-attention. However, this flexibility incurs a computational

Enabling AI-Native Mobility in 6G: A Real-World Dataset for Handover, Beam Management, and Timing Advance

arXiv:2605.12453v1 Announce Type: cross Abstract: To address the issues of high interruption time and measurement report overhead under user equipment (UE) mobility especially in high speed 5G use cas

Agents

Encore: Conditioning Trajectory Forecasting via Biased Ego Rehearsals

arXiv:2605.11463v1 Announce Type: new Abstract: Learning and representing the subjectivities of agents has become a challenging but crucial problem in the trajectory prediction task. Such subjectiviti

agentsarxiv-cs-cv

Enhancing Domain Generalization in 3D Human Pose Estimation through Controllable Generative Augmentation

arXiv:2605.12198v1 Announce Type: new Abstract: Pedestrian motion, due to its causal nature, is strongly influenced by domain gaps arising from discrepancies between training and testing data distribu

applicationsarxiv-cs-cv

EPIC: Efficient Predicate-Guided Inference-Time Control for Compositional Text-to-Image Generation

arXiv:2605.11722v1 Announce Type: new Abstract: Recent text-to-image (T2I) generators can synthesize realistic images, but still struggle with compositional prompts involving multiple objects, counts,

local-aiarxiv-cs-cv

Expected Batch Optimal Transport Plans and Consequences for Flow Matching

arXiv:2605.12174v1 Announce Type: new Abstract: Solving optimal transport (OT) on random minibatches is a common surrogate for exact OT in large-scale learning. In flow matching (FM), this surrogate i

From Observations to States: Latent Time Series Forecasting

arXiv:2602.00297v2 Announce Type: replace Abstract: Deep learning has achieved strong performance in Time Series Forecasting (TSF). However, we identify a critical representation paradox, termed Laten

tutorialsarxiv-cs-lg

GATA2Floor: Graph attention for floor counting in street-view facades

arXiv:2605.11863v1 Announce Type: new Abstract: Automated analysis of building facades from street-level imagery has great potential for urban analytics, energy assessment, and emergency planning. How

Grounding by Remembering: Cross-Scene and In-Scene Memory for 3D Functional Affordances

arXiv:2605.11616v1 Announce Type: new Abstract: Functional affordance grounding requires more than recognizing an object: an agent must localize the specific region that supports an interaction, such

local-aiarxiv-cs-cv

Hindsight Hint Distillation: Scaffolded Reasoning for SWE Agents from CoT-free Answers

arXiv:2605.11556v1 Announce Type: cross Abstract: Solving complex long-horizon tasks requires strong planning and reasoning capabilities. Although datasets with explicit chain-of-thought (CoT) rationa

IGV-RRT: Prior-Real-Time Observation Fusion for Active Object Search in Changing Environments

arXiv:2603.21887v2 Announce Type: replace Abstract: Object Goal Navigation (ObjectNav) in temporally changing indoor environments is challenging because object relocation can invalidate historical sce

applicationsarxiv-cs-ro

Internalizing Curriculum Judgment for LLM Reinforcement Fine-Tuning

arXiv:2605.11235v1 Announce Type: new Abstract: In LLM Reinforcement Fine-Tuning (RFT), curriculum learning drives both efficiency and performance. Yet, current methods externalize curriculum judgment

Learning density ratios in causal inference using Bregman-Riesz regression

arXiv:2510.16127v2 Announce Type: replace-cross Abstract: The ratio of two probability density functions is a fundamental quantity that appears in many areas of statistics and machine learning, includ

tutorialsarxiv-cs-lg

Localising Dropout Variance in Twin Networks

arXiv:2507.03622v2 Announce Type: replace Abstract: Accurate individual treatment-effect estimation demands not only reliable point predictions but also uncertainty measures that help practitioners lo

MambaNetBurst: Direct Byte-level Network Traffic Classification without Tokenization or Pretraining

arXiv:2605.11034v1 Announce Type: cross Abstract: We present MambaNetBurst, a compact tokenizer-free byte-level sequence classifier for network burst classification based on a Mamba-2 backbone. In con

researcharxiv-cs-lg

Monitoring access to piped water and sanitation infrastructure in Africa at disaggregated scales using satellite imagery and self-supervised learning

arXiv:2411.19093v4 Announce Type: replace Abstract: Access to drinking water and sanitation services is essential for health and well-being, yet large global disparities persist. Sustainable Developme

MotionGRPO: Overcoming Low Intra-Group Diversity in GRPO-Based Egocentric Motion Recovery

arXiv:2605.05680v2 Announce Type: replace Abstract: This paper studies full-body 3D human motion recovery from head-mounted device signals. Existing diffusion-based methods often rely on global distri

local-aiarxiv-cs-cv

Neural Statistical Functions

arXiv:2605.11327v1 Announce Type: new Abstract: Classical deep learning typically operates on individual cases. Despite its success, real-world usage often requires repeated inference to estimate stat

OmniHumanoid: Streaming Cross-Embodiment Video Generation with Paired-Free Adaptation

arXiv:2605.12038v1 Announce Type: new Abstract: Cross-embodiment video generation aims to transfer motions across different humanoid embodiments, such as human-to-robot and robot-to-robot, enabling sc

applicationsarxiv-cs-cv

Physics-Informed Teacher-Student Ensemble Learning for Traffic State Estimation with a Varying Speed Limit Scenario

arXiv:2605.11346v1 Announce Type: new Abstract: Physics-informed deep learning (PIDL) neural networks have shown their capability as a useful instrument for transportation practitioners in utilizing t

local-aiarxiv-cs-lg

PointGS: Semantic-Consistent Unsupervised 3D Point Cloud Segmentation with 3D Gaussian Splatting

arXiv:2605.11520v1 Announce Type: new Abstract: Unsupervised point cloud segmentation is critical for embodied artificial intelligence and autonomous driving, as it mitigates the prohibitive cost of d

safetyarxiv-cs-cv

Post-ADC Inference: Valid Inference After Active Data Collection

arXiv:2605.11511v1 Announce Type: cross Abstract: The validity of statistical inference depends critically on how data are collected. When data gathered through active data collection (ADC) are reused

Agents

Random-Set Graph Neural Networks

arXiv:2605.11987v1 Announce Type: cross Abstract: Uncertainty quantification has become an important factor in understanding the data representations produced by Graph Neural Networks (GNNs). Despite

agentsarxiv-cs-lg

Read, Extract, Classify: A Tool for Smarter Requirements Engineering

arXiv:2605.11045v1 Announce Type: cross Abstract: This paper presents the ReXCL tool, which automates the extraction and classification processes in requirements engineering, enhancing the software de

researcharxiv-cs-lg