Search: “multimodal”

GSM8K-V: Can Vision Language Models Solve Grade School Math Word Problems in Visual Contexts

arXiv:2509.25160v2 Announce Type: replace-cross Abstract: Mathematical reasoning is a key capability for vision-language models (VLMs), yet current benchmarks mainly evaluate text-based or explicitly

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Invocation-Level Reliability of Tool-Using Agents

DGX agent

arXiv:2608.26189v1 Announce Type: new Abstract: Tool-using agents fail two ways: choosing the wrong tool, or forming wrong arguments, and an early failure of either kind can silently corrupt everythin

model-releasesarxiv-cs-ai

28 Aug 2026

Applications

Multi-Image Visual Token Pruning in Large Visual Language Models

arXiv:2608.26806v1 Announce Type: new Abstract: With the growing demand for processing multiple image sequences in real-world applications, various visual token pruning methods have emerged to mitigat

applicationsarxiv-cs-cv

SHIFT: Semantic Harmonization via Index-side Feature Transformation for Multilingual Information Retrieval

arXiv:2606.18801v2 Announce Type: replace-cross Abstract: With the rapid expansion of massive multilingual corpora, Multilingual Information Retrieval (MLIR) has emerged as a critical technology for g

safetyarxiv-cs-ai

Local Ai

UniGeo: A Multi-modal Large Language Model for Text-Guided Cross-View Geo-Localization

arXiv:2608.26722v1 Announce Type: new Abstract: Text-guided drone geo-localization aims to identify a target region in a large-scale image gallery from a natural-language description. Existing methods

local-aiarxiv-cs-cv

Align Then Adapt: Label-Efficient Adapter Learning for Asymmetric Dense Retrieval

arXiv:2604.03403v2 Announce Type: replace-cross Abstract: Dense retrieval systems increasingly face an asymmetry between complex instruction-like queries and relatively simple, static document collect

researcharxiv-cs-cl

Asymmetric Cross-Modal Fine-Grained Visual Categorization: ACF-Net and the BirdPro Benchmark

arXiv:2608.25520v1 Announce Type: new Abstract: Audio-visual cross-modal Fine-Grained Visual Categorization (FGVC) aims to identify fine-grained categories by jointly leveraging visual and auditory in

Automatic weld seam segmentation for industrial quality control: a comparison of RGB and polarimetric imaging with CNN and transformer architectures

arXiv:2608.25465v1 Announce Type: new Abstract: Visual inspection of welded assemblies remains one of the least automated stages in many industrial production processes, still depending largely on the

BRIDLE: Generalized Self-supervised Learning with Quantization

arXiv:2502.02118v2 Announce Type: replace-cross Abstract: Self-supervised learning has been a powerful approach for learning meaningful representations from unlabeled data across various domains, redu

DCEO: Direct Causal Effect Optimization for Long-Term User Value Modeling in E-commerce Search

arXiv:2608.25635v1 Announce Type: new Abstract: Industrial e-commerce search systems ultimately aim to optimize the user-level long-term objective, such as n-day cumulative purchases or gross merchand

safetyarxiv-cs-lg

Drift Variation Autoencoder: Unifying Generation and Representation Learning through Conditional Posterior Flow Matching

model-releasesarxiv-cs-lg

arXiv:2608.25138v1 Announce Type: new Abstract: Stochastic masking, cropping, or modality removal makes deterministic reconstruction an incomplete target: one observation can admit many clean completi

MLLMCLIP: Feature-Level Distillation of MLLM for Robust Vision-Language Representations

arXiv:2608.25575v1 Announce Type: new Abstract: Pretrained vision-language models such as CLIP excel at zero-shot recognition but often fail at compositionality, particularly attribute-object and rela

Overview of SHROOM-Visions 2026: A Shared Task on Hallucination Detection in Large Vision-Language Models

arXiv:2608.25662v1 Announce Type: new Abstract: In 2026, we held the fourth iteration of the SHROOM Shared Task series: SHROOM-Visions (extbf{S}hared-task on extbf{H}allucinations and extbf{R}elated e

researcharxiv-cs-cl

PARAssist: A Framework for Personalized and Adaptive Robotic Assistance from Ambiguous User Requests

arXiv:2608.24905v1 Announce Type: cross Abstract: Service robots may encounter ambiguous user requests that require context-aware inference. Users may also have unique preferences with certain tasks w

researcharxiv-cs-ro

SelfGraphRAG: Bridging the Supervision Gap in Graph-Based RAG with Synthetic QA Generation

arXiv:2608.25123v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves large language models by incorporating external knowledge without retraining, but existing methods often u

researcharxiv-cs-cl

Agents

Synergistic Modality-and-Slice Memory Framework for Cross-Modal 3D Brain Tumor Segmentation

arXiv:2510.10679v2 Announce Type: replace Abstract: The 3D multi-modal brain tumor segmentation is critical to multi-modal healthcare, and it requires accurate identification of distinct internal anat

agentsarxiv-cs-cv

Applications

TacForcing: Streaming Action Generation with Execution-Time Tactile Feedback

arXiv:2608.25798v1 Announce Type: cross Abstract: Contact-rich manipulation requires adapting to contact states that can evolve substantially within an action horizon. However, chunk-based vision-lang

applicationsarxiv-cs-lg

Agents

TAU-Agent: An Agentic Retrieval-Augmented Framework for Traffic Anomaly Understanding

arXiv:2608.25935v1 Announce Type: new Abstract: Traffic Anomaly Understanding (TAU) requires models and systems to detect, reason about, and explain anomalous events in transportation videos. To addre

agentsarxiv-cs-cv

Think-Probe-Respond: Improving Large Language Models as Judges of Research Idea Novelty

arXiv:2608.25660v1 Announce Type: new Abstract: Automated novelty judgment can accelerate scientific discovery by enabling efficient evaluation, refinement, and comparison of research ideas. While lar

safetyarxiv-cs-cl

VBVR-Pro: A Scalable and Verifiable Suite for Native Visual Reasoning

arXiv:2608.26105v1 Announce Type: new Abstract: Native visual reasoning treats visual generation as the medium of reasoning itself: visual states (i.e. images and videos) are not merely inputs to be u

VGA-BenchV2: An Expanded Unified Benchmark and Multi-Model Framework for Evaluating Video Aesthetics and Generation Quality

arXiv:2608.25452v1 Announce Type: new Abstract: We introduce VGA-BenchV2, an extended human-aligned benchmark and optimization framework for jointly evaluating and improving video generation quality a

VisDocAgentBench: Benchmarking Agents for Visually Rich Document Retrieval

arXiv:2608.17889v1 Announce Type: cross Abstract: Visually rich documents encode relevance through language, layout, structured visual elements, and corpus context, yet retrieval is typically evaluate

Adaptive prediction theory combining offline and online learning

model-releasesarxiv-cs-lg

arXiv:2512.00342v2 Announce Type: replace Abstract: Real-world intelligence systems usually operate by combining offline learning and online adaptation with highly correlated and non-stationary system

BioKERN: Biological Kernel Regularization for Histology-to-Transcriptomics Neighborhood Retrieval

arXiv:2608.24823v1 Announce Type: new Abstract: Spatially resolved biology requires representations that preserve biological neighborhood structure rather than only exact cross-modal correspondences.

safetyarxiv-cs-lg

CARE: Camera-Residual Reserves for First Sightings in Adaptive LiDAR Sensing

arXiv:2608.24282v1 Announce Type: new Abstract: Adaptive LiDAR scanning concentrates a limited sensing budget on regions of interest predicted from past object tracks, lowering data volume in autonomo

DRRG: A Discrete Diffusion Framework for Radiology Report Generation

arXiv:2608.24105v1 Announce Type: new Abstract: Purpose: Automatic radiology report generation (RRG) has been widely explored to improve reporting accuracy and reduce radiologists' workload. Most exis

Example-based Robust Abnormality Detection with Minimal Annotations using Exemplar Med-DETR

arXiv:2608.24281v1 Announce Type: new Abstract: Reducing annotation requirements remains a key challenge in developing robust medical object detectors. To address this, Vision-Language (VL) object det

Graph-Supervised Hierarchical Clinical Alignment for Radiology Report Generation with Large Language Models

arXiv:2608.24121v1 Announce Type: new Abstract: Radiology report generation (RRG) has recently benefited from large language models, which substantially improve report fluency. However, clinically fai

HAP: Head-Adaptive Visual Token Pruning via Cross-Modal Alignment

arXiv:2608.23921v1 Announce Type: new Abstract: Recent Vision-Language Models encode high-resolution images into long visual token sequences, incurring prohibitive prefill costs. To compress them, exi

Human-Inspired Social Engagement Analysis via Interpretable Mutual Visual Attention

arXiv:2608.24580v1 Announce Type: new Abstract: Understanding social interactions from non-verbal visual data is important for behavior analysis and activity monitoring. We propose an interpretable co

MnemoDyn: Learning Resting State Dynamics from 40K FMRI sequences

arXiv:2608.23936v1 Announce Type: new Abstract: We present a dynamical-systems based model for resting-state functional magnetic resonance imaging (rs-fMRI), trained on a dataset of roughly 40K rs-fMR

researcharxiv-cs-lg

Panning for Gold: Expanding Domain-Specific Knowledge Graphs with General Knowledge

arXiv:2601.10485v5 Announce Type: replace Abstract: Domain-specific knowledge graphs (DKGs) are critical yet often suffer from limited coverage compared to General Knowledge Graphs (GKGs). Existing ta

researcharxiv-cs-ai

PlaceSeek: Human-Centered Geospatial Retrieval of Urban Outdoor Places via Semantic Grounding and Affective Alignment

arXiv:2608.24133v1 Announce Type: cross Abstract: People search for urban outdoor places not only by category or function, but also by what activities a place can support and how it is perceived. Exis

safetyarxiv-cs-ai

Local Ai

RefineRank: Joint Box Refinement and Ranking for Surgical Spatio-Temporal Grounding

arXiv:2608.23928v1 Announce Type: cross Abstract: Surgical spatio-temporal grounding (STG) requires locating, at each video time specified by a procedural question, the object that the question asks a

local-aiarxiv-cs-ai

RENDER: Controlling Reader-Facing Evidence in LLM Memory Evaluation

arXiv:2608.23568v1 Announce Type: new Abstract: Memory and RAG evaluations often treat the answering model's input as an implementation detail, even though systems may render the same history as a mem

TRACE: An Evidence-Grounded Benchmark for Safety Evaluation of Large Reasoning Models

arXiv:2608.24232v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) generate intermediate reasoning traces that may contain unsafe content, even when their final responses appear safe. Guard

VGGT-DP: Generalizable Robot Control via Vision Foundation Models

arXiv:2509.18778v2 Announce Type: replace-cross Abstract: Visual imitation learning frameworks allow robots to learn manipulation skills from expert demonstrations. While existing approaches mainly fo

safetyarxiv-cs-ai

Boosting Knowledge-based Visual Question Answering with Structured Context Reasoning

arXiv:2608.21431v1 Announce Type: new Abstract: Knowledge-based Visual Question Answering aims to answer questions about an image by integrating external knowledge with visual and textual information.

Entity-Constrained CBCT Retrieval for Low-Resource Dental Record Completion

arXiv:2608.21913v1 Announce Type: new Abstract: Completing dental records from cone-beam computed tomography (CBCT) is difficult when annotation is scarce and individual clinical fields are supported

EviSafe: Evidence-Grounded Safety Evaluation for Vision-Language Models

arXiv:2608.23313v1 Announce Type: new Abstract: Vision-language model safety benchmarks typically evaluate only final responses: whether a model refuses, warns, or complies. This outcome-level view ca

Agents

Ludi{}_{scriptscriptstyle 0.1}: An Agentic System for Socially Intelligent Robots

arXiv:2608.22035v1 Announce Type: new Abstract: Robot foundation models have substantially advanced perception and control, but natural human-robot collaboration requires more than executing isolated

agentsarxiv-cs-ro

Predicting Multiple Clinical Outcomes Related to Functional Recovery and Social Isolation Among Older Adults After Lower-Limb Fracture or Hip Replacement

arXiv:2608.23531v1 Announce Type: new Abstract: Older adults recovering after lower-limb fracture or hip replacement may experience complex recovery trajectories. Most of the time, these clinical aspe

Why Personalization Matters: Cross-Subject Challenges in EMG-IMU-based HRI Activity Recognition

arXiv:2608.21620v1 Announce Type: new Abstract: This paper investigates wearable-based recognition of human activities and gestures to support Human-Robot Interaction (HRI) in object-handover and asse

researcharxiv-cs-ro

Amplifying the imaging power of digital sky surveys with space telescopes data and generative AI

arXiv:2608.20666v1 Announce Type: cross Abstract: While Digital sky surveys provide excellent throughput of image data and can cover a large footprint, their imaging power is normally inferior to that

researcharxiv-cs-ai

Anchoring Instruction Outside Mask: Exact Reference Caching for Efficient In-Context Diffusion Transformers

arXiv:2608.21229v1 Announce Type: new Abstract: Omnimodal generation is central to a wide range of content creation and editing applications. In-context conditioning is essential to this paradigm. It

Don't Judge Code by Its Cover: Exploring Biases in LLM Judges for Code Evaluation

arXiv:2505.16222v2 Announce Type: replace Abstract: With the growing use of large language models(LLMs) as evaluators, their application has expanded to code evaluation tasks, where they assess the co

safetyarxiv-cs-cl

Dynamic Context Scheduling: Learning Beyond the Static Universe

arXiv:2608.20799v1 Announce Type: new Abstract: We study dynamic context scheduling as a training instrument for contextual re- inforcement learning. Rather than treating intra-episode context variati

Explainable Deepfake Detection with Feature-robust Augmentation and Evidence-grounded Explanation Optimization

arXiv:2608.20913v1 Announce Type: cross Abstract: Explainable deepfake detection extends binary classification by requiring models to not only predict authenticity but also provide interpretable justi

researcharxiv-cs-ai