Search: “evaluation”

Quantum-Enhanced Similarity Measures for Polarimetric Materials Classification

arXiv:2606.07766v1 Announce Type: cross Abstract: We present a quantum--classical hybrid pipeline for polarimetric material classification that casts this as a point-matching problem. Voxel cubes, con

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Model Releases

Quantum feature-map learning with reduced resource overhead

DGX agent

arXiv:2510.03389v2 Announce Type: replace-cross Abstract: Current quantum computers require algorithms that use limited resources economically. In quantum machine learning, success hinges on quantum f

model-releasesarxiv-cs-lg

9 Jun 2026

RAILS: Verification-Native Clearing For Agentic Commerce

arXiv:2606.08790v1 Announce Type: new Abstract: Autonomous agents negotiate, purchase, deploy code, and move funds, but no neutral mechanism determines whether they met their delegated obligation, who

agentsarxiv-cs-ai

Applications

Real-Time and Accurate Collision-Free Teleoperation via Differentiable Constraint-Based Trajectory Planning

arXiv:2606.08725v1 Announce Type: new Abstract: In teleoperation, the human operator typically controls only the end-effector pose, which often leads to self-collisions of the manipulator and collisio

applicationsarxiv-cs-ro

Reason Twice: Segmentation via Candidate Discovery and Comparative Reasoning

model-releasesarxiv-cs-cv

arXiv:2606.09303v1 Announce Type: new Abstract: The rapid development of pretrained foundation models has enabled more general image segmentation. Multimodal large language models (MLLMs) have been wi

Reasoning Arena: Trace Tournaments When Verifiable Rewards Fall Short

arXiv:2606.09380v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a leading paradigm for improving the reasoning ability of large language models throu

Reconstructing Synthetic SDO/AIA 193 A EUV Images from He I 10830 A Observations with Diffusion Model Translator

arXiv:2606.08652v1 Announce Type: cross Abstract: Routine full-disk EUV imaging has been available only since the modern era, such as SOHO and SDO. To extend EUV coronal context into earlier periods,

ReGIL: Retrieval-Guided Imitation Learning from a Single Demonstration

arXiv:2606.09381v1 Announce Type: new Abstract: Learning robot manipulation policies with deep neural networks from a single demonstration remains highly challenging, as even small deviations from the

safetyarxiv-cs-ro

Region-Wise Correspondence Prediction between Manga Line Art Images

arXiv:2509.09501v4 Announce Type: replace Abstract: Understanding region-wise correspondences between manga line art images is fundamental for high-level manga processing, supporting downstream tasks

safetyarxiv-cs-cv

Report on CHIIR 2026 Workshop on Generative AI and Academic Search (GAI&AS)

arXiv:2606.08936v1 Announce Type: cross Abstract: This report summarizes the CHIIR 2026 Workshop on Generative AI and Academic Search (GAI&AS), which examined how GenAI is reshaping academic search sy

RetroReasoner: A Reasoning LLM for Strategic Retrosynthesis Prediction

arXiv:2603.12666v2 Announce Type: replace-cross Abstract: Retrosynthesis prediction aims to identify reactants that can synthesize a given product molecule. Although molecular large language models (L

Revisiting Training Scale: An Empirical Study of Token Count, Power Consumption, and Parameter Efficiency

arXiv:2601.06649v2 Announce Type: replace-cross Abstract: Research in machine learning has questioned whether increases in training token counts reliably produce proportional performance gains in larg

Reward Evolution with Graph-of-Thoughts: A Bi-Level Language Model Framework for Reinforcement Learning

arXiv:2509.16136v5 Announce Type: replace Abstract: Designing effective reward functions remains a major challenge in reinforcement learning (RL), often requiring considerable human expertise and iter

agentsarxiv-cs-ro

Tutorials

RGB-S: Image-Aligned Tactile Saliency for Robust Dexterous Manipulation

arXiv:2606.08765v1 Announce Type: cross Abstract: Effective visuo-tactile integration is critical for robotic dexterous manipulation, especially when visual observations are unreliable or occluded. Ho

tutorialsarxiv-cs-cv

Robust In-Context Reinforcement Learning Under Reward Poisoning Attacks

arXiv:2506.06891v3 Announce Type: replace Abstract: We study the corruption-robustness of in-context reinforcement learning (ICRL), focusing on the Decision-Pretrained Transformer (DPT, Lee et al., 20

researcharxiv-cs-lg

Robust Renal Mass Segmentation on CT: A Validation Study of an AI-Based Framework

arXiv:2505.07573v2 Announce Type: replace-cross Abstract: Renal mass segmentation has important potential to enhance the clinical workflow, especially in settings requiring quantitative assessments. K

RunAgent SuperBrowser: A Theory of Autonomous Web Navigation Grounded in Human Browsing Behaviour

arXiv:2606.09399v1 Announce Type: new Abstract: We present SUPERBROWSER, an autonomous web-navigation agent designed against a single guiding hypothesis: a web agent should browse the way a person bro

Safe, Fluent and Acceptable Motion Generation and Execution for Human--Robot Interaction in Manufacturing Environments

arXiv:2606.08741v1 Announce Type: new Abstract: Robots operating in human environments must not only ensure physical safety but also exhibit behaviors that are understandable, fluent, and acceptable t

safetyarxiv-cs-ro

SafeECGMatch: Calibration-Aware Joint Frequency and Time Space Semi-Supervised Learning for Open-Set ECG Classification

arXiv:2606.08037v1 Announce Type: cross Abstract: Electrocardiogram (ECG) classification models often suffer from severe label scarcity, making semi-supervised learning (SSL) an attractive strategy fo

SC3: The Multi-Solvent Solubility Challenge and Benchmark

arXiv:2606.07656v1 Announce Type: cross Abstract: Solubility prediction is a standard benchmark in computational chemistry, yet multi-solvent models which reportedly approach the experimental-noise ce

Scaling Decision-Focused Learning to Large Problems with Lagrangian Decomposition

arXiv:2606.08797v1 Announce Type: cross Abstract: Decision-focused learning has shown great promise for addressing predict-then-optimize problems, particularly in the presence of under-specified model

scCBGM: Interpretable Single-Cell Counterfactual Editing

arXiv:2606.07760v1 Announce Type: new Abstract: Understanding cellular phenotypes and how they respond to perturbations is critical for disease biology and therapeutic design. Single-cell RNA sequenci

SciTrace: Trajectory-Aware Safety Reasoning for Scientific Discovery Agents

arXiv:2606.08234v1 Announce Type: new Abstract: LLM-based scientific agents have shown strong capacity for autonomous research, yet their safety layers remain structurally divorced from core reasoning

safetyarxiv-cs-ai

Securing Self-supervised Data Curation for Foundation Models Robustness

arXiv:2606.09511v1 Announce Type: new Abstract: Self-supervised data curation provides a pathway to scaling and improving the generalization capabilities of machine learning models. By leveraging self

researcharxiv-cs-cv

Local Ai

Seeing the Hivemind: A Consensus-Aware Interaction Technique for Mitigating AI Homogenization

arXiv:2606.09587v1 Announce Type: cross Abstract: People are increasingly using AI for creative tasks such as writing. While adoption continues to grow, this form of use risks undermining individual c

local-aiarxiv-cs-ai

SegmentAnyTreeV2: Scaling Transformer-Based Tree Instance Segmentation Across Sensors, Platforms, and Forests

model-releasesarxiv-cs-cv

arXiv:2606.08206v1 Announce Type: new Abstract: We present SegmentAnyTreeV2, a sensor- and platform-agnostic framework for semantic and instance segmentation of forest point clouds. The model combines

Self-Supervised Learning with a Multi-Task Latent Space Objective

arXiv:2602.05845v2 Announce Type: replace Abstract: We propose a multi-task formulation of self-predictive Siamese SSL in which each spatial transformation defines a distinct latent-space alignment ta

safetyarxiv-cs-cv

Semantic Quorum Assurance: Collective Certification for Non-Deterministic AI Infrastructure

arXiv:2606.08021v1 Announce Type: cross Abstract: As large language model (LLM) agents are integrated into autonomous cloud operations, distributed systems face a semantic reliability problem: propose

safetyarxiv-cs-ai

SENTRY: Statistical Reliability Analysis of Vision Transformers Under Soft Errors

arXiv:2606.07620v1 Announce Type: cross Abstract: With the growth of Vision Transformers in safety-critical domains like autonomous systems and medical imaging, ensuring their reliability against soft

Shape Formation for the Cooperative Transportation of Arbitrary Objects Using Multi-Agent Reinforcement Learning

arXiv:2606.09610v1 Announce Type: cross Abstract: Cooperative object transportation is essential in numerous domains, including industrial to domestic services. A popular transportation strategy is to

agentsarxiv-cs-ai

Shared Semantics, Divergent Mechanisms: Unsupervised Feature Discovery by Aligning Semantics and Mechanisms

arXiv:2606.08236v1 Announce Type: cross Abstract: As large language models are increasingly deployed in high-stakes settings, there is a growing need for tools that audit not only model outputs but al

researcharxiv-cs-lg

SIGA: Self-Evolving Coding-Agent Adapters for Scientific Simulation

arXiv:2606.09774v1 Announce Type: new Abstract: Advanced scientific simulators expose specialized input languages that turn simulation goals into executable configurations, but learning them can cost

agentsarxiv-cs-ai

Signals Are Not States: Neuro-Symbolic Safeguards for Culturally Aware Classroom AI

arXiv:2603.22793v2 Announce Type: replace Abstract: Classroom AI systems increasingly infer high-level educational states such as engagement, confusion, collaboration, participation, and instructional

Applications

Simultaneous hyperkinetic movement disorders phenotyping: a cross-cohort pediatric transfer study using routine videos, markerless pose estimation and a tabular foundation model

arXiv:2606.07674v1 Announce Type: new Abstract: Objective: To develop and externally test a video-based framework for simultaneous detection of hyperkinetic MDs phenomenologies: dystonia, tremor, myoc

applicationsarxiv-cs-cv

Local Ai

SMART: Shot-Aware Multimodal Video Moment Retrieval with Audio-Enhanced MLLM

arXiv:2511.14143v2 Announce Type: replace-cross Abstract: Video Moment Retrieval is a task in video understanding that aims to localize a specific temporal segment in an untrimmed video based on a nat

local-aiarxiv-cs-ai

Tutorials

SmartMixed: A Two-Phase Training Strategy for Adaptive Activation Function Learning in Neural Networks

arXiv:2510.22450v3 Announce Type: replace-cross Abstract: The choice of activation function plays a critical role in neural networks, yet most architectures still rely on fixed, uniform activation fun

tutorialsarxiv-cs-ai

SMI: Efficient Self-Supervised Learning via Mutual-Information-Inspired Dependency Optimization

arXiv:2606.08332v1 Announce Type: new Abstract: Self-supervised learning (SSL) has achieved remarkable representation learning performance, but many existing methods rely on large batch sizes, memory

safetyarxiv-cs-cv

SNN-MLIR: An MLIR Dialect for Compiling Neuromorphic SNNs from NIR to Bare-Metal C

arXiv:2606.09213v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) are increasingly trained in a wide range of frameworks (SnnTorch, Lava, Norse, and others) each with its own model form

Hardware

SoccerNet 2026 Player-Centric Ball-Action Spotting:Retraining and Post-Processing Extensions to the FOOTPASS Baselines

arXiv:2606.09679v1 Announce Type: new Abstract: We describe our system for the SoccerNet 2026 Player-Centric Ball-Action Spotting Challenge, which requires predicting who performs which action and whe

hardwarearxiv-cs-cv

SoK: Reconstruction Attacks on Synthetic Tabular Data (Insights from Winning the NIST CRC)

arXiv:2606.08372v1 Announce Type: cross Abstract: Synthetic data is increasingly promoted as a privacy-preserving substitute for releasing sensitive tabular records, yet its central adversarial threat

Solving Inverse Problems with Flow-based Models via Model Predictive Control

arXiv:2601.23231v2 Announce Type: replace-cross Abstract: Flow-based generative models provide strong unconditional priors for inverse problems, but guiding their dynamics for conditional generation r

Speaker-Invariant Representation Learning for Spoofing Detection via Gradient Reversal and A Variational Information Bottleneck

arXiv:2606.08678v1 Announce Type: cross Abstract: Sophisticated generative speech technology can undermined the reliability of voice biometrics. While spoofing detection systems excel when assessed un

safetyarxiv-cs-lg

Tutorials

SpectraLDS: Provable Distillation for Linear Dynamical Systems

arXiv:2505.17868v2 Announce Type: replace Abstract: We present the first provable method for identifying symmetric linear dynamical systems (LDS) with accuracy guarantees that are independent of the s

tutorialsarxiv-cs-lg

SPIN: Decentralized Swarm Control via Tensorized Policy Coordination

arXiv:2606.07557v1 Announce Type: new Abstract: Decentralized multi-agent swarm coordination on resource-constrained edge platforms remains fundamentally bottlenecked by the exponential scaling of joi

safetyarxiv-cs-lg

Stable and Scalable Probabilistic Numerical Solvers for Stiff and High-Dimensional ODEs

arXiv:2606.08203v1 Announce Type: cross Abstract: Filtering-based probabilistic numerical solvers for ordinary differential equations (ODEs) have been established as a flexible and efficient simulatio

researcharxiv-cs-lg

Hardware

STAR-KV: Low-Rank KV Cache Compression via Soft Thresholding for Adaptive Rank Control

arXiv:2606.08382v1 Announce Type: cross Abstract: Low-rank projection has emerged as a promising approach for compressing the KV cache by exploiting hidden-dimension redundancy. However, prior methods

hardwarearxiv-cs-ai

STAR: Rethinking MoE Routing as Structure-Aware Subspace Learning

arXiv:2606.08814v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) scales model capacity efficiently by selectively routing inputs to a specialized subset of experts. However, input-expert speci

Steer Where It Matters: Token-Level Visual-Sensitivity Steering for LVLMs Hallucination Mitigation

arXiv:2606.07647v1 Announce Type: new Abstract: Large vision language models (LVLMs) have made rapid advancements and are deployed across various applications, yet hallucinations remain a major challe

researcharxiv-cs-cv