Search: “multimodal”

AgroVisNet: A lightweight Convolutional Network and the BD-PlantDX Expert-Validated Benchmark for Radish, Potato and Pointed Gourd Disease Classification

arXiv:2609.10469v1 Announce Type: new Abstract: Automated plant disease diagnosis is increasingly deployed on farmer-held devices in regions where agronomic expertise is scarce and network connectivit

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Bayesian deep learning integration of geophysical and drilling data for 3D prediction of copper mineralization and drill targeting: a case study from the Kogodai prospect, Rudny Altai

arXiv:2609.09246v1 Announce Type: cross Abstract: Exploration drill targeting in structurally complex terranes is hindered by sparse sampling, heterogeneous datasets, and the ambiguity of geophysical

applicationsarxiv-cs-lg

Beyond Similarity: Foundation Models as an Efficient Backbone for Training-Free Composed Video Retrieval

arXiv:2609.10008v1 Announce Type: new Abstract: Composed video retrieval (CoVR) searches a gallery for the target video that realizes a natural-language modification of a source clip. However, at gall

Tutorials

BrainTaskonomy: Learning How to Pretrain and What to Transfer in fMRI Foundation Models

arXiv:2609.10518v1 Announce Type: new Abstract: fMRI foundation models increasingly aggregate heterogeneous data across brain states, cohorts, and acquisition settings, yet pretraining domains are com

tutorialsarxiv-cs-cv

ConvMem: Convolutional Memory for Long-Context Reasoning

arXiv:2609.10441v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have demonstrated impressive capabilities, they often struggle with extremely long contexts due to fixed context li

researcharxiv-cs-cl

CriticGen: Generation-Aware Evaluation as Actionable Feedback

arXiv:2609.05439v1 Announce Type: new Abstract: Current evaluation methods for large language models are coarse-grained and decoupled from generation, producing generic explanations that fail to provi

researcharxiv-cs-ai

DAREBench: Deployment-Aware and Reliable Evaluation of Models as Agents

arXiv:2609.06059v1 Announce Type: new Abstract: As large language models evolve from question-answering systems into general-purpose agents, evaluation must move beyond static answer correctness to as

DSAEval: Evaluating Data Science Agents on a Wide Range of Real-World Data Science Problems

arXiv:2601.13591v3 Announce Type: replace Abstract: Recent LLM-based data agents aim to automate data science tasks ranging from data analysis to deep learning. However, the open-ended nature of real-

Forgetting Only What Matters: Layer-Selective Unlearning toward Robust LLMs

model-releasesarxiv-cs-lg

arXiv:2609.10439v1 Announce Type: new Abstract: Large Language Models (LLMs) can memorize and reproduce sensitive, copyrighted, or otherwise undesirable training content, creating privacy, safety, and

Applications

Freezing of Gait Prediction Under Spatial Occlusion: An IMU-Supervised Cross-Modal Distillation Approach

arXiv:2609.09826v1 Announce Type: new Abstract: Parkinson's disease is a progressive neurodegenerative disorder characterised by gradual deterioration of movement control. Automated freezing-of-gait (

applicationsarxiv-cs-cv

Inferring the Unspoken: Aligning Embodied Agents with Implicit Preferences

arXiv:2502.00858v4 Announce Type: replace Abstract: Natural-language instructions rarely specify every detail required for embodied action. An agent asked to ``prepare an apple,'' for example, must st

Infra-Bench CLS: A Global, Open-Source Benchmark for Critical Infrastructure Classification with Earth Observation Foundation Models

arXiv:2609.09482v1 Announce Type: new Abstract: Critical infrastructure location data is often incomplete and unevenly distributed globally, especially in developing regions. Earth observation foundat

Lensless Gaze Is Not Private by Default: Auditing Identity Leakage Across Disclosure Surfaces

arXiv:2609.09188v1 Announce Type: new Abstract: Lensless near-eye sensing is often described as privacy-friendly because its coded measurements are visually unintelligible. Yet visual unintelligibilit

MemForest: Efficient Agent Memory Management via EventTree Partitioning and Progressive Merging

arXiv:2609.08273v1 Announce Type: new Abstract: Agent memory systems have demonstrated significant potential in long-term dialogue, personalized assistants, and video understanding. However, continuou

agentsarxiv-cs-ai

Neptune: An AI model for Global Ocean Subseasonal Prediction

arXiv:2609.08606v1 Announce Type: cross Abstract: Subseasonal-to-seasonal (S2S) forecasting is societally critical, supporting decision-making in sectors ranging from water and agricultural management

researcharxiv-cs-ai

ObGynLongBench: Revealing the Evidence-to-EHR Gap in Longitudinal EHR Decision-Making

arXiv:2609.07601v1 Announce Type: cross Abstract: The application of large language models (LLMs) to personalized medical assistants has garnered growing interest. However, existing medical benchmarks

Performance of Clinical AI System and Physicians and Frontier Language Models in primary care diagnostics

arXiv:2609.09070v1 Announce Type: cross Abstract: Clinical AI evaluation should encompass diagnosis and management after adaptive information gathering. We compared Doctorina, eight physicians and fou

Personalizing LLM Agent Memory Using Biometrics

arXiv:2609.08558v1 Announce Type: new Abstract: Personalized memory helps LLM agents deliver stable, tailored assistance by storing and reusing user-specific data across interactions. In multi-user sc

agentsarxiv-cs-ai

Precision in Rice Variety Classification using Stacking-Based Ensemble Learning

arXiv:2609.10524v1 Announce Type: new Abstract: Rice, a staple food for a significant portion of the global population, exhibits remarkable diversity in its varieties, presenting substantial challenge

Quality Metrics for LLM-Generated Asset Administration Shells: A Perturbation-Based Evaluation Approach

arXiv:2609.07290v1 Announce Type: cross Abstract: The rapid digital transformation of manufacturing, often referred to as Industry 4.0, relies on seamless interoperability between physical and softwar

Qwen-Audio-3.0-ASR Technical Report

model-releasesarxiv-cs-cl

arXiv:2609.07549v2 Announce Type: replace Abstract: In recent years, automatic speech recognition (ASR) has witnessed transformative advancements driven by three complementary paradigms: data scaling,

Spot-the-shift: Evaluating Grounded Image Difference Captioning of Long-term Changes

arXiv:2609.10356v1 Announce Type: new Abstract: Long-term change understanding from images of the same place revisited over time is a challenging task with applications in map maintenance and urban in

Substrate-Portable Execution for Production LLM Workflows

arXiv:2609.06128v1 Announce Type: new Abstract: Production LLM agents execute tool-calling loops, retrieval chains, and compositional workflows in multiple modes, yet execution semantics are often cou

agentsarxiv-cs-ai

Video-MOPD: Multi-Teacher On-Policy Distillation for Video Understanding

arXiv:2609.09300v1 Announce Type: new Abstract: Video understanding demands a convergence of complementary capabilities across perception, temporal understanding, and complex reasoning, which are diff

xDailyBench: Benchmarking LLMs on Professional Consultation for Real-Life Problems

arXiv:2609.07784v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for everyday assistance, yet existing benchmarks only partially reflect the requests users naturally

A Survey on Adversarial Attacks and Defenses for Diffusion Models Across Multiple Modalities

arXiv:2609.05503v1 Announce Type: new Abstract: Diffusion models have become the dominant family of generative models in the visual domain. However, their widespread public availability enables misuse

A Two-Stage Framework for Ego-Centric Key Object Identification via Object State Prediction

arXiv:2609.07125v1 Announce Type: new Abstract: This paper presents a novel framework designed to enhance key object identification in autonomous driving. Existing methods primarily focus on either de

agentsarxiv-cs-cv

Ambient @ EgoProactive 2026 : Proactive Egocentric Assistance with Visually Grounded Supervision

arXiv:2609.07099v1 Announce Type: new Abstract: We present our submission to the EgoProactive track of the ECCV 2026 Wearable AI Challenge, which ranked first in the large-model division and second in

An overview of 3D Vision-Language Models

arXiv:2609.05583v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are reshaping computer vision by aligning visual and textual embeddings, allowing models to recognize visual concepts and

Applications

AtomicVLA: Unlocking the Potential of Atomic Skill Learning in Robots

arXiv:2603.07648v2 Announce Type: replace-cross Abstract: Recent advances in Visual-Language-Action (VLA) models have shown promising potential for robotic manipulation tasks. However, real-world robo

applicationsarxiv-cs-cv

Attention-Enhanced Deep Features with Heterogeneous Ensemble Learning for Glaucoma Detection

arXiv:2609.06699v1 Announce Type: new Abstract: Glaucoma is a progressive optic neuropathy characterized by irreversible damage to the optic nerve, making timely diagnosis critical to prevent permanen

Local Ai

BlueprintAgent: Constraint-Triggered Targeted Revisits for Simulation-Ready Generation from Scanned Structural Blueprints

arXiv:2609.07362v1 Announce Type: cross Abstract: Converting in-service reinforced-concrete (RC) building blueprints into simulation-ready models---structured frame representations that support determ

local-aiarxiv-cs-cv

Companion-style QA Assistance in Ego-Vision

arXiv:2609.06721v1 Announce Type: new Abstract: AI companions are envisioned as always-on assistants that support users in daily life. With this regard, we introduce BuddyVQA, a benchmark for companio

Tutorials

Comparative Study of Anatomical and Learned Features in AI Models for Structural Brain MRI

arXiv:2609.06807v1 Announce Type: new Abstract: In this work, we comprehensively evaluate three popular feature-extraction paradigms in AI-based neuroimaging modeling: (1) computation of anatomical su

tutorialsarxiv-cs-cv

Concentrate After Imagination: Text-Conditioned Evidence Grounding for Partially Relevant Video Retrieval

arXiv:2609.08999v1 Announce Type: new Abstract: Partially Relevant Video Retrieval (PRVR) retrieves untrimmed videos when queries describe only short moments. Although recent methods improve local rep

ContextFlow: In-Context Flow Matching for Robot Manipulation

arXiv:2609.06852v1 Announce Type: new Abstract: Although highly effective in vision and language domains, applying in-context learning to robotics remains challenging. Existing autoregressive in-conte

researcharxiv-cs-ro

Continuous Token-Level Spatio-Temporal Context Modeling for Visual Object Tracking

arXiv:2609.07070v1 Announce Type: new Abstract: Spatio-temporal context has become increasingly crucial for visual tracking. However, most existing approaches extract spatio-temporal cues via discrete

Contrastive Knowledge Distillation for Anomaly Detection in Multi-Illumination/Focus Display Images

arXiv:2609.05520v1 Announce Type: new Abstract: In this paper, we tackle automatic anomaly detection in multi-illumination and multi-focus display images. The minute defects on the display surface are

DIVA: Exploiting Cross-Step Conditional Propagation for Visual Jailbreaks in Discrete Diffusion Vision-Language Models

arXiv:2609.05525v1 Announce Type: new Abstract: Large vision-language models (VLMs) are increasingly deployed in safety-critical settings, yet existing visual jailbreak research has focused almost exc

Facial Age Estimation for Age Fraud Detection in National ID Systems

arXiv:2609.05638v1 Announce Type: new Abstract: Identity fraud during biometric enrollment and updates remains a major challenge for large-scale national identity systems. A common fraud vector is mis

Federated Binary Gating with Server-Side Vision-Language Inference for Surveillance Anomaly Classification

arXiv:2609.07403v1 Announce Type: new Abstract: Privacy-sensitive surveillance systems could benefit from large vision-language models (VLMs), but such models typically require centralized access to r

HB-PVI: A Hierarchical Bayesian Personalization and Value-of-Information Framework for Complex Activity Recognition

arXiv:2609.05582v1 Announce Type: new Abstract: Personalization can improve activity-recognition performance, but participant-specific gains are heterogeneous, and every additional calibration label h

safetyarxiv-cs-lg

Hi-FLoop: Hierarchical State-Feedback Loops for Multi-Timescale World Modeling

arXiv:2609.08796v1 Announce Type: new Abstract: Multi-agent traffic simulation seeks diverse, coordinated, and physically realistic futures from maps and observed history. Long-horizon closed-loop gen

agentsarxiv-cs-cv

Infrastructure-based Monocular 3D Vehicle Localization Framework with Experimental Validation

arXiv:2609.05523v1 Announce Type: new Abstract: This paper presents a one-stage learning framework that maps monocular roadside-camera images directly to vehicle states in a ground-fixed coordinate fr

Knowing When Not to Answer: Abstention and Refusal Reasoning in Vision--Language Models

arXiv:2609.05540v1 Announce Type: new Abstract: Many medical conditions require diagnosis through detailed, multi-context clinical assessment rather than from visual appearance alone. Despite this, vi

MARS-CLIP: Multi-Resolution and Attention Refined Zero-Shot Image Segmentation

arXiv:2609.08283v1 Announce Type: new Abstract: Contrastive Language-Image Pre-training (CLIP) has demonstrated impressive capabilities in zero-shot transfer but often struggles with dense prediction

MCANet: A Multi-Scale Class-Specific Attention Network for Multi-Label Post-Hurricane Damage Assessment Using UAV Imagery

arXiv:2509.04757v2 Announce Type: replace Abstract: Hurricanes cause widespread damage to buildings, roads, and other infrastructure, making timely post-disaster damage assessment critical for emergen

Observing Health Outcomes Using Remote Sensing Imagery and Geo-Context Guided Visual Transformer

arXiv:2602.00110v2 Announce Type: replace Abstract: Visual transformers have driven major progress in remote sensing image analysis, particularly in object detection and segmentation. Recent vision-la