Search: “multimodal”

OphMAE: Bridging Volumetric and Planar Imaging with a Foundation Model for Adaptive Ophthalmological Diagnosis

arXiv:2605.02714v1 Announce Type: new Abstract: The advent of foundation models has heralded a new era in medical artificial intelligence (AI), enabling the extraction of generalizable representations

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Research

Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning

DGX agent

arXiv:2605.00973v1 Announce Type: new Abstract: Biosignals acquired from different locations on the body often provide temporally ordered views of the same underlying physiological process. However, m

researcharxiv-cs-lg

5 May 2026

SurgTEMP: Temporal-Aware Surgical Video Question Answering with Text-guided Visual Memory for Laparoscopic Cholecystectomy

arXiv:2603.29962v3 Announce Type: replace Abstract: Surgical procedures are inherently complex and risky, requiring extensive expertise and constant focus to navigate evolving intraoperative scenes. C

safetyarxiv-cs-cv

The Geometric Mechanics of Contrastive Representation Learning: Alignment Potentials, Entropic Dispersion, and Cross-modal Divergence

arXiv:2601.19597v3 Announce Type: replace Abstract: While InfoNCE underlies modern contrastive learning, its geometric mechanisms remain under-characterized beyond the canonical alignment--uniformity

safetyarxiv-cs-lg

Towards Visual Query Localization in the 3D World

arXiv:2605.01498v1 Announce Type: new Abstract: Visual query localization (VQL) aims to predict the spatio-temporal response of the most recent occurrence in a sequence given a query. Currently, most

Understanding the Performance Plateau in Text-to-Video Retrieval: A Comprehensive Empirical and Linguistic Analysis

arXiv:2605.00826v1 Announce Type: cross Abstract: Text-to-video retrieval enables users to find relevant video content using natural language queries, a task that has grown increasingly important with

Generating Statistical Charts with Validation-Driven LLM Workflows

arXiv:2605.00800v1 Announce Type: new Abstract: Generating diverse, readable statistical charts from tabular data remains challenging for LLMs, as many failures become apparent after rendering and are

researcharxiv-cs-lg

4 May 2026

Let ViT Speak: Generative Language-Image Pre-training

arXiv:2605.00809v1 Announce Type: new Abstract: In this paper, we present extbf{Gen}erative extbf{L}anguage-extbf{I}mage extbf{P}re-training (GenLIP), a minimalist generative pretraining framework for

4 May 2026

AEGIS: A Holistic Benchmark for Evaluating Forensic Analysis of AI-Generated Academic Images

arXiv:2604.28177v1 Announce Type: new Abstract: We introduce AEGIS, A holistic benchmark for Evaluating forensic analysis of AI-Generated academic ImageS. Compared to existing benchmarks, AEGIS featur

AI Models for Depressive Disorder Detection and Diagnosis: A Review

arXiv:2508.12022v2 Announce Type: replace Abstract: Major Depressive Disorder is one of the leading causes of disability worldwide, yet its diagnosis still depends largely on subjective clinical asses

safetyarxiv-cs-ai

Applications

Context as Prior: Bayesian-Inspired Intent Inference for Non-Speaking Agents with a Household Cat Testbed

arXiv:2604.27445v1 Announce Type: new Abstract: Many agents in real-world environments cannot reliably communicate their goals through language, including household pets, pre-verbal infants, and other

applicationsarxiv-cs-cv

Decoding Scientific Experimental Images: The SPUR Benchmark for Perception, Understanding, and Reasoning

arXiv:2604.27604v1 Announce Type: new Abstract: We introduce SPUR, a comprehensive benchmark for scientific experimental image perception, understanding, and reasoning, comprising 4,264 question-answe

Imitation Game for Adversarial Disillusion with Chain-of-Thought Reasoning in Generative AI

arXiv:2501.19143v2 Announce Type: replace Abstract: As the cornerstone of artificial intelligence, machine perception confronts a fundamental threat posed by adversarial illusions. These adversarial a

agentsarxiv-cs-ai

MotuBrain: An Advanced World Action Model for Robot Control

arXiv:2604.27792v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models achieve strong semantic generalization but often lack fine-grained modeling of world dynamics. Recent work explores

safetyarxiv-cs-ro

Simulating Infant First-Person Sensorimotor Experience via Motion Retargeting from Babies to Humanoids

arXiv:2604.27583v1 Announce Type: cross Abstract: Motion retargeting from humans to human-like artificial agents is becoming increasingly important as humanoid robots grow more capable. However, most

researcharxiv-cs-ro

DenseStep2M: A Scalable, Training-Free Pipeline for Dense Instructional Video Annotation

arXiv:2604.26565v1 Announce Type: new Abstract: Long-term video understanding requires interpreting complex temporal events and reasoning over procedural activities. While instructional video corpora,

Electricity price forecasting across Norway's five bidding zones in the post-crisis era

model-releasesarxiv-cs-lg

arXiv:2604.26634v1 Announce Type: new Abstract: Norway's electricity market is heavily dominated by hydropower, but the 2021--2022 energy crisis and stronger integration with Continental Europe have f

Perception Test 2025: Challenge Summary and a Unified VQA Extension

arXiv:2601.06287v2 Announce Type: replace Abstract: The Third Perception Test challenge was organised as a full-day workshop alongside the IEEE/CVF International Conference on Computer Vision (ICCV) 2

Topology-Aware Representation Alignment for Semi-Supervised Vision-Language Learning

arXiv:2604.26370v1 Announce Type: new Abstract: Vision-language models have shown strong performance, but they often generalize poorly to specialized domains. While semi-supervised vision-language lea

safetyarxiv-cs-cv

Agentic AI for Remote Sensing: Technical Challenges and Research Directions

arXiv:2604.24919v1 Announce Type: new Abstract: Earth Observation (EO) is moving beyond static prediction toward multi-step analytical workflows that require coordinated reasoning over data, tools, an

agentsarxiv-cs-cv

An analysis of sensor selection for fruit picking with suction-based grippers

arXiv:2604.24906v1 Announce Type: cross Abstract: Robotic fruit harvesting often fails to reliably detect whether a fruit has been successfully picked, limiting efficiency and increasing crop damage.

researcharxiv-cs-lg

BEVal: A Cross-dataset Evaluation Study of BEV Segmentation Models for Autonomous Driving

arXiv:2408.16322v4 Announce Type: replace Abstract: Current research in semantic bird's-eye view segmentation for autonomous driving focuses solely on optimizing neural network models using a single d

agentsarxiv-cs-cv

Calibrated Fusion for Heterogeneous Graph-Vector Retrieval in Multi-Hop QA

arXiv:2603.28886v2 Announce Type: replace-cross Abstract: Graph-augmented retrieval combines dense similarity with graph-based relevance signals such as Personalized PageRank (PPR), but these scores h

researcharxiv-cs-lg

Control Your Queries: Heterogeneous Query Interaction for Camera-Radar Fusion

arXiv:2604.25574v1 Announce Type: new Abstract: In autonomous driving, camera-radar fusion offers complementary sensing and low deployment cost. Existing methods perform fusion through input mixing, f

agentsarxiv-cs-cv

CRC-SAM: SAM-Based Multi-Modal Segmentation and Quantification of Colorectal Cancer in CT, Colonoscopy, and Histology Images

arXiv:2604.24793v1 Announce Type: cross Abstract: We present CRC-SAM, a unified framework for colorectal cancer segmentation across colonoscopy, CT, and histopathology images. Unlike prior single-moda

FGDM: Reasoning Aware Multi-Agentic Framework for Software Bug Detection using Chain of Thought and Tree of Thought Prompting

arXiv:2604.24831v1 Announce Type: cross Abstract: Deep Learning methods are becoming prominent in automated software bug detection; however, they lack the global understanding of the given code. Conse

agentsarxiv-cs-lg

Images Amplify Misinformation Sharing in Vision-Language Models

model-releasesarxiv-cs-cl

arXiv:2505.13302v2 Announce Type: replace Abstract: As language and vision-language models (VLMs) become central to information access and online interaction, concerns grow about their potential to am

Learning from Noisy Preferences: A Semi-Supervised Learning Approach to Direct Preference Optimization

arXiv:2604.24952v1 Announce Type: new Abstract: Human visual preferences are inherently multi-dimensional, encompassing aesthetics, detail fidelity, and semantic alignment. However, existing datasets

safetyarxiv-cs-cv

MiMo-Embodied: X-Embodied Foundation Model Technical Report

arXiv:2511.16518v2 Announce Type: replace-cross Abstract: We open-source MiMo-Embodied, the first cross-embodied foundation model to successfully integrate and achieve state-of-the-art performance in

agentsarxiv-cs-cl

SlicerRoboTMS: An Open-Source 3D Slicer Extension for Robot-Assisted Transcranial Magnetic Stimulation

arXiv:2604.25661v1 Announce Type: new Abstract: Robot-assisted Transcranial Magnetic Stimulation (Robo-TMS) is an image-guided robotic intervention that enhances the accuracy and reproducibility of co

researcharxiv-cs-ro

Local Ai

2nd of the 5th PVUW MeViS-Audio Track: ASR-SaSaSa2VA

arXiv:2604.23935v1 Announce Type: new Abstract: Audio-based video object segmentation aims to locate and segment objects in videos conditioned on audio cues, requiring precise understanding of both ap

local-aiarxiv-cs-cv

Local Ai

A Dynamic Learning Observatory Reveals the Rapid Salinization of Satkhira, Bangladesh

arXiv:2604.23127v1 Announce Type: cross Abstract: Soil salinity is a major environmental challenge in coastal Bangladesh, threatening agricultural productivity and local livelihoods. This study develo

local-aiarxiv-cs-lg

A Heterogeneous Two-Stream Framework for Video Action Recognition with Comparative Fusion Analysis

arXiv:2604.23415v1 Announce Type: new Abstract: Most two-stream action recognition networks apply the same convolutional backbone to both RGB and optical flow streams, ignoring the fact that the two m

Applications

A Hierarchical Ensemble Inference Pipeline for Robust White Blood Cell Classification Under Domain Shifts

arXiv:2604.23271v1 Announce Type: new Abstract: Automated white blood cell (WBC) classification is essential for scalable leukaemia screening. However, real-world deployment is challenged by domain sh

applicationsarxiv-cs-cv

Accelerating New Product Introduction for Visual Quality Inspection via Few-Shot Diffusion-Based Defect Synthesis

arXiv:2604.22850v1 Announce Type: new Abstract: Industrial visual inspection systems often suffer from a severe scarcity of labeled defect data, particularly during the early stages of New Product Int

AdaComp: Extractive Context Compression with Adaptive Predictor for Retrieval-Augmented Large Language Models

arXiv:2409.01579v2 Announce Type: replace-cross Abstract: Retrieved documents containing noise will hinder RAG from detecting answer clues and make the inference process slow and expensive. Therefore,

Advancing Remote Medical Palpation through Cognition and Emotion

arXiv:2407.05595v3 Announce Type: replace Abstract: Medical palpation is more than force transmission. It is a bidirectional cognitive and emotional exchange between doctor and patient. We model two c

researcharxiv-cs-ro

BrickNet: Graph-Backed Generative Brick Assembly

arXiv:2604.22984v1 Announce Type: new Abstract: We train a language model to generate LEGO-brick build sequences. While prior work has been restricted to discrete, voxel-like towers, we consider a muc

DVPO: Distributional Value Modeling-based Policy Optimization for LLM Post-Training

arXiv:2512.03847v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has shown strong performance in LLM post-training, but real-world deployment often involves noisy or incomplete su

safetyarxiv-cs-ai

Enabling Transparent Cyber Threat Intelligence Combining Large Language Models and Domain Ontologies

arXiv:2509.00081v2 Announce Type: replace-cross Abstract: Effective Cyber Threat Intelligence (CTI) relies upon accurately structured and semantically enriched information extracted from cybersecurity

agentsarxiv-cs-ai

Exploring Audio Hallucination in Egocentric Video Understanding

arXiv:2604.23860v1 Announce Type: cross Abstract: Egocentric videos provide a distinctive setting in which sound serves as crucial cues to understand user activities and surroundings, particularly whe

Focus on What Matters: Two-Stage ROI-Aware Refinement for Anatomy-Preserving Fetal Ultrasound Reconstruction

arXiv:2604.23839v1 Announce Type: cross Abstract: Measurement-critical ultrasound tasks often depend on a small anatomical region, making global reconstruction metrics an unreliable proxy for clinical

GA2-CLIP: Generic Attribute Anchor for Efficient Prompt Tuningin Video-Language Models

arXiv:2511.22125v2 Announce Type: replace Abstract: Visual and textual soft prompt tuning can effectively improve the adaptability of Vision-Language Models (VLMs) in downstream tasks. However, fine-t

Hard to See, Hard to Label: Generative and Symbolic Acquisition for Subtle Visual Phenomena

arXiv:2604.22990v1 Announce Type: cross Abstract: Subtle visual anomalies such as hairline cracks, sub-millimeter voids, and low-contrast inclusions are structurally atypical yet visually ambiguous, m

Identity-Decoupled Anonymization for Visual Evidence in Multi-modal Retrieval-Augmented Generation

arXiv:2604.23584v1 Announce Type: new Abstract: Multi-modal retrieval-augmented generation (MRAG) systems retrieve visual evidence from large image corpora to ground the responses of large multi-modal

In-depth Analysis of Graph-based RAG in a Unified Framework

arXiv:2503.04338v2 Announce Type: replace-cross Abstract: Graph-based Retrieval-Augmented Generation (RAG) has proven effective in integrating external knowledge into large language models (LLMs), imp

researcharxiv-cs-cl

K-SENSE: A Knowledge-Guided Self-Augmented Encoder for Neuro-Semantic Evaluation of Mental Health Conditions on Social Media

arXiv:2604.23493v1 Announce Type: cross Abstract: Early detection of mental health conditions, particularly stress and depression, from social media text remains a challenging open problem in computat

KARL: Mitigating Hallucinations in LLMs via Knowledge-Boundary-Aware Reinforcement Learning

arXiv:2604.22779v1 Announce Type: cross Abstract: Enabling large language models (LLMs) to appropriately abstain from answering questions beyond their knowledge is crucial for mitigating hallucination

agentsarxiv-cs-ai