Search: “evaluation”

Tactile-based Multimodal Fusion in Embodied Intelligence: A Survey of Vision, Language, and Contact-Driven Paradigms

arXiv:2605.17336v1 Announce Type: cross Abstract: Tactile sensing is a fundamental modality for embodied intelligence, offering unique and direct feedback on contact geometry, material properties, and

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TailedTS: Benchmark Dataset for Heavy-Tailed Time Series Prediction and Periodicity Quantification

DGX agent

arXiv:2605.16361v1 Announce Type: cross Abstract: We present TailedTS, a large-scale benchmark dataset derived from Wikipedia hourly page view observations throughout 2024, specifically designed to te

model-releasesarxiv-cs-ai

19 May 2026

TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models

arXiv:2605.17577v1 Announce Type: new Abstract: Large-scale pre-trained Vision-Language models (VLMs), such as CLIP, exhibit strong zero-shot generalization, yet remain highly vulnerable to impercepti

Taming Audio VAEs via Target-KL Regularization

arXiv:2605.17085v1 Announce Type: cross Abstract: Latent diffusion models have emerged as the dominant paradigm for many generation tasks including audio generation such as text-to-audio, text-to-musi

Task Abstention for Large Language Models in Code Generation

arXiv:2605.17029v1 Announce Type: cross Abstract: Large language models (LLMs) have revolutionized automated code generation. One serious concern, however, is the so-called ``hallucination'', i.e., LL

Task-Level AI Readiness Assessment for Business Process Management:The T-IPO Model and LARA Matrix in Financial-Services IT Operations

arXiv:2605.16297v1 Announce Type: cross Abstract: Which tasks inside an enterprise workflow can a large-language-model agent reliably handle, and under what conditions? Most business process modeling

Hardware

TeleRAG: Efficient Retrieval-Augmented Generation Inference with Lookahead Retrieval

arXiv:2502.20969v4 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) extends large language models (LLMs) with external data sources to enhance factual correctness and domain

hardwarearxiv-cs-lg

Temporal Decay of Co-Citation Predictability: A 20-Year Statute Retrieval Benchmark from 396M Ukrainian Court Citations

model-releasesarxiv-cs-cl

arXiv:2605.17639v1 Announce Type: new Abstract: Co-citation structure is widely assumed to provide stable retrieval signal in legal information systems. We test this assumption longitudinally by const

Test-Time Hinting for Black-Box Vision-Language Models

arXiv:2605.16410v1 Announce Type: new Abstract: Test-time scaling (TTS) methods have proven highly effective for LLMs, yet their application to vision-language models (VLMs) remains relatively underex

The Alien Space of Science: Sampling Coherent but Cognitively Unavailable Research Directions

arXiv:2603.01092v2 Announce Type: replace Abstract: Scientific discovery is constrained not only by what is true, but by what is cognitively available to the researchers currently exploring a field. M

The Alpha Illusion: Reported Alpha from LLM Trading Agents Should Not Be Treated as Deployment Evidence

arXiv:2605.16895v1 Announce Type: cross Abstract: End-to-end LLM trading agents have moved quickly from research curiosity to a small ecosystem of named systems, including FinCon, FinMem, TradingAgent

The End of Trust: How Agentic AI Breaks Security Assumptions

arXiv:2605.16436v1 Announce Type: cross Abstract: For decades, the security of digital interaction has rested on an unacknowledged economic constraint. Attackers faced a tradeoff between the fidelity

The Geometry of Projection Heads: Conditioning, Invariance, and Collapse

arXiv:2605.17180v1 Announce Type: new Abstract: We develop a geometric theory of projection heads in self-supervised learning by modeling the head as a trainable Riemannian metric on the backbone repr

Tutorials

The Learnability Gap in Medical Latent Diffusion

arXiv:2605.17087v1 Announce Type: new Abstract: Generative data augmentation with latent diffusion models is a promising strategy for addressing class imbalance in medical imaging, yet current approac

tutorialsarxiv-cs-cv

Local Ai

The Point of No Return: Counterfactual Localization of Deceptive Commitment in Language-Model Reasoning

arXiv:2605.17113v1 Announce Type: cross Abstract: Existing deception datasets label completed outputs as honest or deceptive, treating deception as a property of the final response rather than a funct

local-aiarxiv-cs-ai

The Score Kalman Filter

arXiv:2605.16644v1 Announce Type: cross Abstract: A central obstacle in nonlinear Bayesian filtering is representing the belief distribution. Moment-based filters address this by propagating polynomia

'The Whole Is Greater Than the Sum of Its Parts': A Compatibility-Aware Multi-Teacher CoT Distillation Framework

arXiv:2601.13992v2 Announce Type: replace-cross Abstract: Chain-of-Thought (CoT) reasoning empowers Large Language Models (LLMs) with remarkable capabilities but typically requires prohibitive paramet

Local Ai

Thinking with Patterns: Breaking the Perceptual Bottleneck in Visual Planning via Pattern Induction

arXiv:2605.16848v1 Announce Type: cross Abstract: Planning from raw visual input remains a significant challenge for current Vision-Language Models (VLMs), when the complexity of input is beyond their

local-aiarxiv-cs-ai

this has probably been the most interesting project i've ever worked on. we created the best agent at finding problems with your agent. and …

this has probably been the most interesting project i've ever worked on. we created the best agent at finding problems with your agent. and we integrated it with the best observability platform to spi

agentsharrison-chase--x

Throughput-Optimal Scheduling Algorithms for LLM Inference and AI Agents

arXiv:2504.07347v3 Announce Type: replace-cross Abstract: As demand for Large Language Models (LLMs) and AI agents grows rapidly, optimizing systems for efficient LLM inference becomes critical. While

agentsarxiv-cs-lg

Hardware

TierCheck: Tiered Checkpointing for Fault Tolerance in Large Language Model Training

arXiv:2605.17821v1 Announce Type: cross Abstract: Large Language Model (LLM) training is frequently interrupted by a heterogeneous spectrum of failures, from common GPU crashes to catastrophic cluster

hardwarearxiv-cs-ai

Time-Efficient Hybrid Hyperparameter Tuning Approach for Cardiovascular Disease Classification

arXiv:2411.18234v2 Announce Type: replace-cross Abstract: Cardiovascular diseases (CVDs) are any serious illness of the heart, which require accurate diagnosis to prevent fatal consequences. Hyperpara

Topo-GS: Continuous Volumetric Embedding of High-Dimensional Data via Topological Gaussian Splatting

arXiv:2605.17011v1 Announce Type: cross Abstract: Dimensionality reduction algorithms map high-dimensional data into visualizable 2D or 3D spaces, but traditionally rely on a discrete point-cloud para

TouchMap-OR: Multi-View 3D Mapping of Hand-Surface Contacts

arXiv:2605.17638v1 Announce Type: new Abstract: Hand-surface interactions between clinicians, patients, and medical equipment play a central role in pathogen transmission during medical procedures. Ho

Toward Near-Real-Time Marine Oil Spill Detection in SAR Imagery using Quantum-Assisted SVM

arXiv:2605.17217v1 Announce Type: cross Abstract: Marine oil spills require rapid detection to mitigate severe ecological and economic damage. While satellite-based Synthetic Aperture Radar (SAR) prov

Towards Migrating Neural Network Implementations

arXiv:2511.02610v2 Announce Type: replace Abstract: The development of smart systems (i.e., systems enhanced with AI components) has thrived thanks to the rapid advancements in neural networks (NNs).

Towards Universal Physical Adversarial Attacks via a Joint Multi-Objective and Multi-Model Optimization Framework

arXiv:2605.17772v1 Announce Type: new Abstract: Physical adversarial attacks often overfit single surrogate models and optimization objectives. While ensemble attacks can mitigate this, existing metho

safetyarxiv-cs-cv

Train the Trainers -- An Agentic AI Framework for Peer-Based Mental Health Support in Battlefield Environments

arXiv:2605.16269v1 Announce Type: cross Abstract: Modern military operations expose soldiers to sustained psychological stress, leading to acute reactions, post-traumatic stress symptoms, and other me

Trajectory-Aware Adaptive Inference in Object Detection Models

arXiv:2605.16397v1 Announce Type: cross Abstract: The increasing integration of sensors in autonomous maritime navigation has led to large-scale multimodal datasets, raising challenges in achieving ef

Transitivity Meets Cyclicity: Explicit Preference Decomposition for Dynamic Large Language Model Alignment

arXiv:2605.17342v1 Announce Type: cross Abstract: Standard RLHF relies on transitive scalar rewards, failing to capture the cyclic nature of human preferences. While some approaches like the General P

TriALS: Triphasic-Aided Liver Lesion Segmentation Benchmark in Non-Contrast CT

arXiv:2605.16572v1 Announce Type: new Abstract: Automated segmentation of liver lesions on non-contrast computed tomography (NCCT) is clinically important but fundamentally challenging, particularly i

Hardware

Truthful Calibration Errors for Multi-Class Prediction

arXiv:2510.06388v2 Announce Type: replace Abstract: Calibrated predictions are useful because their numerical values can be interpreted as probabilities. Calibration errors are therefore widely used t

hardwarearxiv-cs-lg

TTE-Flash: Accelerating Reasoning-based Multimodal Representations via Think-Then-Embed Tokens

arXiv:2605.16638v1 Announce Type: new Abstract: Recent research has demonstrated that Universal Multimodal Embedding (UME) benefits significantly from Chain-of-Thought (CoT) reasoning. In this paradig

UniAlign: A Model-Agnostic Framework for Robust Network Traffic Classification under Distribution Shifts

arXiv:2605.17575v1 Announce Type: cross Abstract: Network traffic classification (NTC) models often suffer severe performance degradation when deployed in real-world environments due to distribution s

Universal Pose Pretraining for Generalizable Vision-Language-Action Policies

arXiv:2602.19710v2 Announce Type: replace Abstract: Existing Vision-Language-Action (VLA) models often suffer from feature collapse and low training efficiency because they entangle high-level percept

safetyarxiv-cs-cv

Unleashing the Representational Power of Fourier Shapes for Attacking Infrared Object Detection

arXiv:2605.17822v1 Announce Type: new Abstract: Infrared object detection is crucial for perception in autonomous driving and surveillance but remains vulnerable to physical adversarial attacks. Unlik

agentsarxiv-cs-cv

Use the Online Network If You Can: Towards Fast and Stable Reinforcement Learning

arXiv:2510.02590v2 Announce Type: replace Abstract: The use of target networks is a popular approach for estimating value functions in deep Reinforcement Learning (RL). While effective, the target net

safetyarxiv-cs-lg

UTOPYA: A Multimodal Deep Learning Framework for Physics-Informed Anomaly Detection and Time-Series Prediction

model-releasesarxiv-cs-lg

arXiv:2605.18188v1 Announce Type: new Abstract: Anomaly detection in batch processes is hindered by transient dynamics, scarce fault labels, and reliance on single-modality sensor data. This work intr

Velocity and stroke rate reconstruction of canoe sprint team boats based on panned and zoomed video recordings

arXiv:2602.22941v2 Announce Type: replace Abstract: Pacing strategies, defined by velocity and stroke rate profiles, are essential for peak performance in canoe sprint. While GPS is the gold standard

Verify-Gated Completion as Admission Control in a Governed Multi-Agent Runtime: A Bounded Architecture Case Study

arXiv:2605.17998v1 Announce Type: cross Abstract: As multi-agent systems move from short interactions to tool-using workflows with specialized roles and persistent state, completion becomes a runtime-

VGGT-CD: Training-Free Robust Registration for 3D Change Detection

arXiv:2605.16859v1 Announce Type: cross Abstract: 3D change detection from multi-view images is essential for urban monitoring, disaster assessment, and autonomous driving. However, existing methods p

VGGT-Occ: Geometry-Grounded and Density-Aware Gated Fusion for 3D Occupancy Prediction

arXiv:2605.16911v1 Announce Type: new Abstract: 3D semantic occupancy prediction requires accurate 2D-to-3D feature lifting, yet current methods restrict camera geometry to initial projections. Subseq

Video Reconstruction using Diffusion-based Image-to-Video Generation with Trajectory Guidance

arXiv:2605.16420v1 Announce Type: new Abstract: This paper addresses the problem of reconstructing missing or dropped frames in top-down drone video of autonomous surface vehicles performing structure

safetyarxiv-cs-cv

Vision Inference Former: Sustaining Visual Consistency in Multimodal Large Language Models

arXiv:2605.18160v1 Announce Type: cross Abstract: In recent years, multimodal large language models (MLLMs) have achieved remarkable progress, primarily attributed to effective paradigms for integrati

VLM-AutoDrive: Post-Training Vision-Language Models for Safety-Critical Autonomous Driving Events

arXiv:2603.18178v2 Announce Type: replace-cross Abstract: The rapid growth of ego-centric dashcam footage presents a major challenge for detecting safety-critical events such as collisions and near-co

Voices in the Loop: Mapping Participatory AI

arXiv:2605.16827v1 Announce Type: new Abstract: Participatory approaches to artificial intelligence are increasingly documented across public, civic, and humanitarian settings, but evidence about how

VolTA-3D: Self-Supervised Learning for Brain MRI using 3D Volumetric Token Alignment

arXiv:2605.16775v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has advanced medical image analysis be enabling learning form large unlabelled data. However, in brain magnetic resonan

WASIL: In-the-Wild Arabic Spoken Interactions with LLMs

arXiv:2605.16364v1 Announce Type: cross Abstract: Large Language Models (LLMs) voice assistants are commonly built as cascaded Automatic Speech recognition (ASR) to LLM systems, where recognition erro

researcharxiv-cs-ai