Search: “framework”

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

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Hardware

VeriCache: Turning Lossy KV Cache into Lossless LLM Inference

DGX agent

arXiv:2605.17613v1 Announce Type: cross Abstract: The large size of the KV cache has become a major bottleneck for serving LLMs with increasing context lengths. In response, many KV cache compression

hardwarearxiv-cs-lg

19 May 2026

Verifier-Guided Code Translation via Meta-Step Decoding

model-releasesarxiv-cs-lg

arXiv:2605.17626v1 Announce Type: new Abstract: Test-time scaling is an important mechanism for improving large language models, especially on tasks with deterministic verifiers. Code translation is a

VerifyMAS: Hypothesis Verification for Failure Attribution in LLM Multi-Agent Systems

model-releasesarxiv-cs-cl

arXiv:2605.17467v1 Announce Type: new Abstract: Large language model-driven multi-agent systems (LLM-MAS) excel at complex tasks, yet unreliable agents remain a key bottleneck to system-level reliabil

VeriHGN: Heterogeneous Graph-Based Congestion Prediction for Chip Layout Verification

arXiv:2603.11075v2 Announce Type: replace-cross Abstract: As Very Large Scale Integration (VLSI) designs continue to scale in size and complexity, layout verification has become a central challenge in

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

View-Aware Semantic Alignment for Aerial-Ground Person Re-Identification

arXiv:2605.18192v1 Announce Type: new Abstract: Aerial-Ground Person Re-Identification (AGPReID) remains highly challenging due to drastic viewpoint variations between drones and fixed cameras. Existi

safetyarxiv-cs-cv

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities

arXiv:2605.16880v1 Announce Type: new Abstract: Multimodal magnetic resonance imaging (MRI) is crucial for brain tumor segmentation, with many methods leveraging its four key modalities to capture com

VISAFF: Speaker-Centered Visual Affective Feature Learning for Emotion Recognition in Conversation

arXiv:2605.18547v1 Announce Type: new Abstract: Emotion Recognition in Conversation (ERC) is essential for effective human-machine interaction, aiming to identify speakers' emotional states in multi-t

applicationsarxiv-cs-ai

Vision Foundation Models as Generalist Tokenizers for Image Generation

arXiv:2605.18390v1 Announce Type: new Abstract: In this work, we explore the largely unexplored direction of building a generalist image tokenizer directly on top of a frozen vision foundation model (

Local Ai

Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation

arXiv:2605.18740v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) still struggle with fine-grained visual understanding, where answers often depend on small but decisive evide

local-aiarxiv-cs-ai

VISTA-Bench: Do Vision-Language Models Really Understand Visualized Text as Well as Pure Text?

arXiv:2602.04802v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) have achieved impressive performance in cross-modal understanding across textual and visual inputs, yet existing bench

VISTA: Triplet-Supervised Video Style Transfer with Diffusion Transformers

arXiv:2605.17312v1 Announce Type: new Abstract: Video style transfer aims to render videos in a target artistic style while preserving content, structure, and motion. While image stylization has advan

Local Ai

VISTA: Variance-Gated Inter-Sequence Test-Time Adaptation for Multi-Sequence MRI Segmentation

arXiv:2605.17433v1 Announce Type: new Abstract: Deploying multi-sequence magnetic resonance imaging (MRI) segmentation models to new clinical environments is challenging due to variations in scanners

local-aiarxiv-cs-cv

Visual Agentic Memory: Enabling Online Long Video Understanding via Online Indexing, Hierarchical Memory, and Agentic Retrieval

arXiv:2605.16481v1 Announce Type: cross Abstract: Long video understanding requires more than large context windows. It also needs a memory mechanism that decides what visual evidence to retain, keeps

Visualizing the Invisible: Generative Visual Grounding Empowers Universal EEG Understanding in MLLMs

arXiv:2605.18172v1 Announce Type: new Abstract: Leveraging the universal representations of pre-trained LLMs and MLLMs offers a promising path toward brain foundation models. However, visually-evoked

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

VoxShield: Protecting 3D Medical Datasets from Unauthorized Training via Frequency-Aware Inter-Slice Disruption

arXiv:2605.17345v1 Announce Type: new Abstract: The release of public 3D medical image segmentation (MIS) datasets accelerates clinical research but simultaneously heightens risks of unauthorized AI m

VVitCutLER: Towards Unsupervised Object Detection and Segmentation in Videos

arXiv:2605.17584v1 Announce Type: new Abstract: Unsupervised pixel-level video understanding remains challenging in real-world scenarios, where motion blur, occlusion, and fast object dynamics often c

applicationsarxiv-cs-cv

WavFlow: Audio Generation in Waveform Space

arXiv:2605.18749v1 Announce Type: cross Abstract: Modern audio generation predominantly relies on latent-space compression, introducing additional complexity and potential information loss. In this wo

We Think, Therefore We Align LLMs to Helpful, Harmless and Honest Before They Go Wrong

model-releasesarxiv-cs-cl

arXiv:2509.22510v3 Announce Type: replace Abstract: Alignment of Large Language Models (LLMs) is the ability to satisfy desired objectives during generation, which is critical for trustworthy deployme

Weakly Supervised Cross-Modal Learning for 4D Radar Scene Flow Estimation

arXiv:2605.18507v1 Announce Type: new Abstract: Due to the difficulty of obtaining ground-truth data for 4D radar scene flow estimation, previous methods typically rely on either self-supervised losse

applicationsarxiv-cs-cv

Weighted Reverse Convolution for Feature Upsampling

arXiv:2605.17472v1 Announce Type: new Abstract: Pre-trained vision foundation models (VFMs) provide strong semantic representations, yet their patch-level features are inherently coarse, limiting thei

What Does the AI Doctor Value? Auditing Pluralism in the Clinical Ethics of Language Models

arXiv:2605.18738v1 Announce Type: new Abstract: Medicine is inherently pluralistic. Principles such as autonomy, beneficence, nonmaleficence, and justice routinely conflict, and such ethical dilemmas

When Dynamics Shift, Robust Task Inference Wins: Offline Imitation Learning with Behavior Foundation Models Revisited

arXiv:2605.17017v1 Announce Type: cross Abstract: Behavior Foundation Models (BFMs) enable scalable imitation learning (IL) by pretraining task-agnostic representations that can be rapidly adapted to

When Is Rank-1 Steering Cheap? Geometry, Granularity, and Budgeted Search

arXiv:2605.16362v1 Announce Type: cross Abstract: Activation steering offers a lightweight way to control LLMs without retraining, but its effectiveness varies sharply across concepts. Prior work ofte

When Personalization Legitimizes Risks: Uncovering Safety Vulnerabilities in Personalized Dialogue Agents

arXiv:2601.17887v2 Announce Type: replace Abstract: Long-term memory enables large language model (LLM) agents to support personalized and sustained interactions. However, most work on personalized ag

When Vision Speaks for Sound

arXiv:2605.16403v1 Announce Type: new Abstract: Despite rapid progress in video-capable MLLMs, we find that their apparent audio understanding in videos is often vision-driven: models rely on visual c

safetyarxiv-cs-cv

White-Box Sensitivity Auditing with Steering Vectors

arXiv:2601.16398v2 Announce Type: replace-cross Abstract: Algorithmic audits are essential tools for examining systems for properties required by regulators or desired by operators. Current audits of

safetyarxiv-cs-cl

Agents

Xiaomi EV World Model: A Joint World Model Integrating Reconstruction and Generation for Autonomous Driving

arXiv:2605.18137v1 Announce Type: new Abstract: This report presents a unified technical system addressing the two core capabilities of world models for autonomous driving: world representation and wo

agentsarxiv-cs-cv

You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations

arXiv:2511.06516v3 Announce Type: replace Abstract: Many LLM applications require only narrow capabilities, yet standard post-training quantization (PTQ) methods allocate precision without considering

researcharxiv-cs-cl

3DEditSafe: Defending 3D Editing Pipelines from Unsafe Generation

arXiv:2605.15398v1 Announce Type: cross Abstract: Recent advances in 3D generative editing, particularly pipelines based on 3D Gaussian Splatting (3DGS), have achieved high-fidelity, multi-view-consis

Hardware

A Few GPUs, A Whole Lotta Scale: Faithful LLM Training Emulation with PrismLLM

arXiv:2605.15617v1 Announce Type: cross Abstract: Large language model (LLM) training today runs on clusters spanning thousands of GPUs. While this scale enables rapid model advances, developing, debu

hardwarearxiv-cs-ai

A Retrieval-Enhanced Transformer for Multi-Step Port-of-Call Sequence Prediction in Global Liner Shipping

arXiv:2605.15937v1 Announce Type: new Abstract: Accurate multi-step port-of-call sequence prediction is vital for tactical resource orchestration and logistical efficiency. However, existing methods s

researcharxiv-cs-lg

A Scalable Nonparametric Continuous-Time Survival Model through Numerical Quadrature

arXiv:2605.16208v1 Announce Type: cross Abstract: Flexible continuous-time survival modeling is critical for capturing complex time-varying hazard dynamics in high-dimensional data; however, training

applicationsarxiv-cs-lg

Ada-Diffuser: Latent-Aware Adaptive Diffusion for Decision-Making

arXiv:2605.16054v1 Announce Type: cross Abstract: Recent work has framed decision-making as a sequence modeling problem using generative models such as diffusion models. Although promising, these appr

AdaEraser: Training-Free Object Removal via Adaptive Attention Suppression

arXiv:2605.15921v1 Announce Type: new Abstract: Object removal aims to eliminate specified objects from images while plausibly inpainting the affected regions with background content. Current training

Adapting Foundation Vision-Language Models to Medical Diagnosis via Query-Driven Expert Bridging

arXiv:2505.21698v3 Announce Type: replace Abstract: Vision-language foundation models achieve promising performance in natural image classification, yet their direct application to medical imaging is

Adaptive Conformal Prediction for Quantum Machine Learning

arXiv:2511.18225v2 Announce Type: replace Abstract: Quantum machine learning seeks to leverage quantum computers to improve upon classical machine learning algorithms. Currently, robust uncertainty qu

researcharxiv-cs-lg

ALSO: Adversarial Online Strategy Optimization for Social Agents

arXiv:2605.15768v1 Announce Type: new Abstract: Social simulation provides a compelling testbed for studying social intelligence, where agents interact through multi-turn dialogues under evolving cont

An Algebraic Exposition of the Theory of Dyadic Morality

arXiv:2605.16153v1 Announce Type: new Abstract: This paper provides an algebraic exposition of the theory of dyadic morality (TDM), a psychological model of moral judgment grounded in a simple two-nod

An LLM-RAG Approach for Healthy Eating Index-Informed Personalized Food Recommendations

arXiv:2605.15213v1 Announce Type: cross Abstract: Diet quality is a leading determinant of chronic disease risk. Advances in artificial intelligence (AI) have enabled food recommendation systems to ad

Antidistillation Fingerprinting

arXiv:2602.03812v2 Announce Type: replace-cross Abstract: Model distillation enables efficient emulation of frontier large language models (LLMs), creating a need for robust mechanisms to detect when

Are VLMs Seeing or Just Saying? Uncovering the Illusion of Visual Re-examination

arXiv:2605.15864v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) often produce self-reflective statements like 'let me check the figure again' during reasoning. Do such statements trigg

researcharxiv-cs-cl

Asking the Right Questions: Improving Reasoning with Generated Stepping Stones

arXiv:2602.19069v2 Announce Type: replace Abstract: Recent years have witnessed tremendous progress in enabling LLMs to solve complex reasoning tasks such as math and coding. As we start to apply LLMs

ASRU: Activation Steering Meets Reinforcement Unlearning for Multimodal Large Language Models

arXiv:2605.15687v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) may memorize sensitive cross-modal information during pretraining, making machine unlearning (MU) crucial. Ex

Agents

Attribute-Grounded Selective Reasoning for Artwork Emotion Understanding with Multimodal Large Language Models

arXiv:2605.15755v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can produce fluent artwork emotion explanations, but they often suffer from attribute flooding: they enumerate

agentsarxiv-cs-cv