Search: “evaluation”

ShopX: A Foundation Model for Intent-to-Item Fulfillment in Agentic Shopping

arXiv:2606.31693v1 Announce Type: cross Abstract: The wave of AI-native applications is moving shopping beyond page- and feed-based browsing toward intent-driven experiences orchestrated by LLM agents

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Model Releases

SkillSpotter: Pose-Aware Multi-View Skilled Action Detection and Grading in Ego-Exo Videos

DGX agent

arXiv:2606.31127v1 Announce Type: cross Abstract: To enable personalized, real-time coaching using Augmented Reality glasses or fixed camera setups in domains such as sports, cooking, or music, a syst

model-releasesarxiv-cs-ai

1 Jul 2026

Smart charging of large fleets of Electric Vehicles: Independent Multi-Agent Reinforcement Learning approaches

arXiv:2606.31347v1 Announce Type: new Abstract: The electrification of transportation through electric vehicles introduces new challenges for power grid management, such as increased peak demand, volt

Stage-Transition Dense Reward Modeling for Reinforcement Learning

arXiv:2606.31377v1 Announce Type: cross Abstract: Reinforcement learning for long-horizon robotic manipulation is often limited by sparse and delayed rewards, while manually designing dense shaping si

Tutorials

Step-by-Step Video-to-Audio Synthesis via Negative Audio Guidance

arXiv:2506.20995v4 Announce Type: replace Abstract: We propose a step-by-step video-to-audio (V2A) generation method that provides finer control over the generation process and more realistic audio sy

tutorialsarxiv-cs-cv

Structure-Regularized Interpretable TCR-Epitope Prediction

arXiv:2606.30902v1 Announce Type: cross Abstract: T cell receptor (TCR)-epitope binding prediction is essential for understanding adaptive immunity and developing immunotherapies. Existing sequence- a

Structured SIR: Efficient and Expressive Importance-Weighted Inference for High-Dimensional Image Registration

arXiv:2603.17415v2 Announce Type: replace-cross Abstract: Image registration is an ill-posed dense vision task, where multiple solutions achieve similar loss values, motivating probabilistic inference

Surprise as a Signal for Plasticity and Metacognition

arXiv:2606.31495v1 Announce Type: new Abstract: We study a single idea across two settings: that a prediction-error signal, computed by a small predictor over the latent space of a frozen encoder, can

Surrogate Fidelity: When Can Open LLMs Explain Closed Ones?

arXiv:2606.32008v1 Announce Type: new Abstract: Mechanistic interpretability (MI) requires full access to model internals, yet the APIs for most widely deployed language models at best expose log-prob

TactX: Learning Shared Tactile Representations Across Diverse Sensors

arXiv:2606.31236v1 Announce Type: new Abstract: Tactile sensors provide critical information for contact-rich manipulation, yet tactile representations and policies remain tightly coupled to each spec

safetyarxiv-cs-ro

TAPE: Tether-Aware Path Planning for Autonomous Exploration of Unknown 3D Cavities Using a Tangle-Compatible Tethered Aerial Robot

arXiv:2606.30817v1 Announce Type: new Abstract: This letter presents the first method for autonomous exploration of unknown cavities in three dimensions (3D) that focuses on minimizing the distance tr

agentsarxiv-cs-ro

TDGT: A Tabular Data Generation Toolkit supporting adaptive GPU-accelerated Bayesian mixture models, diffusion-based models, and latent-space generative modeling

arXiv:2606.31268v1 Announce Type: cross Abstract: The growing demand for privacy-preserving data sharing has positioned synthetic data generation as a critical component of responsible AI workflows. D

Temporal Training Strategies for Left Atrium and Left Atrial Appendage Segmentation in Dynamic Contrast 4DCT

arXiv:2606.31444v1 Announce Type: new Abstract: Dynamic contrast-enhanced cardiac CT enables time-resolved analysis of contrast filling and washout in the left atrium (LA) and left atrial appendage (L

Test-Time Verification for Text-to-SQL via Outcome Reward Models

arXiv:2606.30851v1 Announce Type: cross Abstract: Improving the reliability of large language models (LLMs) at inference time is a central challenge in structured reasoning tasks such as Text-to-SQL.

The Calibration Turn in AI-Assisted Research: A Conceptual and Methodological Framework for Evidence-Licensed Claims

arXiv:2606.31273v1 Announce Type: new Abstract: AI-assisted research has entered a stage in which the central question is not only whether systems can generate hypotheses, run experiments, or produce

The Impact of Dimensionality on the Stability of Node Embeddings

arXiv:2604.08492v2 Announce Type: replace Abstract: Previous work has shown that node embedding methods can produce different representations and downstream predictions across repeated training runs,

researcharxiv-cs-lg

The Label Imitation Game: Turing Test Network for Zero-Shot Pseudo-Label Pruning

arXiv:2606.30875v1 Announce Type: cross Abstract: Foundation model pseudo-labeling - labeling data strictly via zero-shot inference - enables massive scale, but performance is undermined by hallucinat

The Past Is Prologue: A Plug-in Controller for Selective Updates in Sequentially Evolving LLM Memory

arXiv:2606.31121v1 Announce Type: new Abstract: Sequentially evolving LLM memory enables agents to reuse past experience, but existing systems usually deploy each locally generated memory update witho

Token-Sparse Medical Multimodal Reasoning via Dual-Stream Reinforcement Learning

arXiv:2606.31599v1 Announce Type: cross Abstract: Vision-language models (VLMs) combining reinforcement learning (RL) ignite remarkable progress in multimodal reasoning, yet still struggle with medica

Applications

Tone-Conditioned Curriculum Learning for Low-Resource Bantu Speech Recognition

arXiv:2606.31642v1 Announce Type: new Abstract: Southern Bantu languages are spoken by over 80 million people, yet current foundation ASR models still produce zero-shot WER above 100%, which limits pr

applicationsarxiv-cs-cl

TotalFM: An Organ-Separated 3D-CT Foundation Model Leveraging Large-Scale Routine Clinical Radiology Data

arXiv:2601.00260v2 Announce Type: replace Abstract: While foundation models in radiology are expected to be applied to various clinical tasks, computational cost constraints remain a major challenge w

Tutorials

Toward AI-Resilient Assessment in Computer Science Courses in an AI-Native World

arXiv:2606.30655v1 Announce Type: cross Abstract: AI-native course assessments in senior computer science courses and related fields should grade students by AI-resilient skill: the ability to achieve

tutorialsarxiv-cs-ai

Toxicity Assessment in Preclinical Histopathology via Class-Aware Mahalanobis Distance for Known and Novel Anomalies

arXiv:2602.02124v2 Announce Type: replace-cross Abstract: Drug-induced toxicity is a leading cause of preclinical and early-clinical failure, making early detection critical. Histopathology is the gol

Truth or Sophistry? LoFa: A Benchmark for LLM Robustness Against Logical Fallacies

model-releasesarxiv-cs-cl

arXiv:2606.31039v1 Announce Type: new Abstract: Large Language Models (LLMs) exhibit strong semantic capabilities, yet their resilience to manipulative linguistic patterns such as logical fallacies re

Unsupervised Thermodynamics of Molecular Diffusion Models: Action-Operator Semantics and Auditable Free-Energy Readout

arXiv:2606.30687v1 Announce Type: cross Abstract: Diffusion models are increasingly utilized for modeling molecular structures and conformational ensembles, yet the thermodynamic meaning of their lear

Verification-Gated Agentic Mission-State Governance for Intelligent Industrial Multi-Robot Systems

arXiv:2606.31339v1 Announce Type: new Abstract: Agentic artificial intelligence is increasingly used to decompose industrial tasks, propose robot actions, and adapt execution plans in dynamic cyber-ph

safetyarxiv-cs-ro

VertiAdaptor: Online Kinodynamics Adaptation for Vertically Challenging Terrain

arXiv:2603.06887v3 Announce Type: replace Abstract: Autonomous driving in off-road environments presents significant challenges due to the dynamic and unpredictable nature of unstructured terrain. Tra

agentsarxiv-cs-ro

Visual Prompt Discovery via Semantic Exploration

arXiv:2603.16250v2 Announce Type: replace-cross Abstract: LVLMs encounter significant challenges in image understanding and visual reasoning, leading to critical perception failures. Visual prompts, w

Visual Semantic Entropy: Do Vision Language Models Recognize Visual Ambiguity?

arXiv:2606.31407v1 Announce Type: cross Abstract: Vision-language models can produce confident answers on visually ambiguous inputs, resulting in biased predictions. Common entropy-based methods, such

Von Mises Based Uncertainty Quantification for Closely Spaced Automotive Radar Targets

arXiv:2606.31473v1 Announce Type: cross Abstract: This work investigates uncertainty-aware deep learning approaches for direction of arrival (DOA) estimation in automotive radar, focusing on probabili

What Counts as an Error? Dual-Reference Benchmarking for Atypical ASR

model-releasesarxiv-cs-cl

arXiv:2606.31112v1 Announce Type: new Abstract: ASR systems have been often reported to underperform on atypical speech. An often conflated compounding factor is the existence of two valid transcripti

What Memory Do GUI Agents Really Need? From Passive Records to Active Task-Driving States

model-releasesarxiv-cs-cv

arXiv:2606.31612v1 Announce Type: new Abstract: Mobile GUI agents increasingly face long-horizon tasks that require reading, updating, and reusing task-relevant data across pages and applications. Exi

What Probing Reveals about Autonomous Driving: Linking Internal Prediction Errors to Ego Planning

arXiv:2606.31106v1 Announce Type: cross Abstract: Large-scale datasets and fast simulators have enabled improvements in driving policies that appear safe and robust, yet strong performance in nominal

When LLMs Read Tables Carelessly: Measuring and Reducing Data Referencing Errors

model-releasesarxiv-cs-ai

arXiv:2606.32029v1 Announce Type: cross Abstract: While large language models (LLMs) perform well on table tasks, they still make data referencing errors (DREs), i.e., incorrectly citing or omitting t

When Regulation Has Memory: Hysteresis and Control Burden in Artificial Agency

arXiv:2606.30975v1 Announce Type: new Abstract: Adaptive agents are usually judged by what they do, but an agent can appear stable while the internal effort required to keep it stable is increasing. T

Who Determines the Meaning of an Emotion? Affective Sovereignty as an Epistemic Consequence of Measurement Limits

arXiv:2606.31442v1 Announce Type: new Abstract: Emotion-sensing AI is rapidly becoming embedded in vehicles, home appliances, dialogue agents, and social infrastructure, giving rise to a sphere in whi

WildProp: Visual Estimation of Wildlife Body Proportions at Scale

arXiv:2606.31125v1 Announce Type: new Abstract: Population-level morphometric measurements underpin ecological and evolutionary studies but traditionally require controlled imaging or physical specime

3D Field of Junctions: A Noise-Robust, Training-Free Structural Prior for Volumetric Inverse Problems

arXiv:2603.02149v2 Announce Type: replace Abstract: Volume denoising is a foundational problem in computational imaging, as many 3D imaging inverse problems face high levels of measurement noise. Insp

A Cognition-Emotion-Personality Framework for Modeling Human-Like Awareness and Behavior in Emergency Evacuations

arXiv:2606.29212v1 Announce Type: new Abstract: Agent-based evacuation simulations are widely used to study crowd behavior during emergencies, but many models rely on assumptions such as perfect event

A Conditional GAN for Tabular Data Generation with Probabilistic Sampling of Latent Subspaces

arXiv:2508.00472v2 Announce Type: replace Abstract: The tabular form constitutes the standard way of representing data in relational database systems and spreadsheets. But, similarly to other forms, t

researcharxiv-cs-lg

A Deep Multiscale Neural Network for Accurate Neurological Disorder Detection from MRI Scans and Real-Time Web Deployment

arXiv:2606.29106v1 Announce Type: cross Abstract: Neurological disorders involve diverse pathologies of the brain and nervous system, making early and accurate detection essential. While many deep CNN

A Probabilistic Approach to Trajectory-Based Optimal Experimental Design

arXiv:2601.11473v2 Announce Type: replace-cross Abstract: We present a novel probabilistic approach for optimal experimental path design. In this approach a discrete path optimization problem is defin

A Task-Driven and Quality-Assured Agent Framework for SAR Data Generation

arXiv:2606.28896v1 Announce Type: cross Abstract: Synthetic aperture radar (SAR) data augmentation is important for improving the generalization of data-driven SAR interpretation models, yet practical

A Unified Framework for Multi-Contact Path Planning in the Rolling Robot Systems

arXiv:2606.29065v1 Announce Type: new Abstract: Rolling motion planning is challenging because rolling contact imposes nonholonomic constraints and the configuration evolves on a curved manifold. The

researcharxiv-cs-ro

a very cool Harbor x LangSmith flow I love to help you “look at the data”: 1. you do evals or rollouts for RL 2. all reward metrics and trac…

a very cool Harbor x LangSmith flow I love to help you “look at the data”: 1. you do evals or rollouts for RL 2. all reward metrics and traces and rollouts get automatically propulates into Experiment

agentsharrison-chase--x

A Zero-Shot Deep Image Prior Framework for Denoising and Deconvolution in Fluorescence Microscopy

arXiv:2606.28431v1 Announce Type: cross Abstract: Fluorescence microscopy images are degraded by noise and diffraction-induced blur, which compromise structural fidelity and limit quantitative analysi

A3M: Adaptive, Adversarial and Multi-Objective Learning for Strategic Bidding in Repeated Auctions

arXiv:2606.28943v1 Announce Type: new Abstract: Learning to bid in repeated multi-unit auctions with bandit feedback poses a fundamental challenge. Existing methods often rely on rigid explore-then-ex

safetyarxiv-cs-cl

AccelAes: Accelerating Diffusion Transformers for Training-Free Aesthetic-Enhanced Image Generation

arXiv:2603.12575v2 Announce Type: replace Abstract: Diffusion Transformers (DiTs) are a dominant backbone for high-fidelity text-to-image generation due to strong scalability and alignment at high res

safetyarxiv-cs-cv