Search: “multimodal”

Shared Geometry As A Rosetta Stone: Cross-Modal Alignment Without Paired Data

arXiv:2610.09411v1 Announce Type: cross Abstract: Multimodal representations enable zero-shot classification and retrieval, but aligning independently trained models usually requires large amounts of

safetyarxiv-cs-cv

8 Oct 2026

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Model Releases

VideoZeroBench: Probing the Limits of Video MLLMs with Spatio-Temporal Evidence Verification

DGX agent

arXiv:2604.01569v2 Announce Type: replace Abstract: Video multimodal large language models achieve strong results on existing benchmarks, but answer accuracy alone does not establish whether they can

model-releasesarxiv-cs-cv

8 Oct 2026

ChartBmkAgent: Harness-Governed Multi-Agent Construction of Chart QA Benchmarks from Sparse Error-Taxonomy Specifications

arXiv:2610.08106v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) advance rapidly, while conventional benchmark development lags behind, delaying investigation of newly observed

7 Oct 2026

Constant-Curvature Sliced Gromov-Wasserstein for Heterogeneous Cross-Curvature Alignment

arXiv:2610.07218v1 Announce Type: new Abstract: Recent advances in representation learning have highlighted the utility of constant-curvature models, such as hyperbolic and spherical spaces, for model

7 Oct 2026

Tutorials

Mu-DisCoCat: A Variational Pipeline for Compositional Generalization on Quantum Processors

arXiv:2610.08131v1 Announce Type: cross Abstract: Achieving compositional concept generalization (CoCoGen), the ability to understand novel situations by recombining learned primitives, remains a fund

tutorialsarxiv-cs-cv

7 Oct 2026

Beyond LLM Serving: Characterizing Vision-Language-Action Workloads for Embodied AI System Design

arXiv:2610.05062v1 Announce Type: cross Abstract: Vision-language-action (VLA) models translate multimodal observations into low-level robot actions. During robot operation, each control period sets a

local-aiarxiv-cs-ro

IRSTD-Agent: Agentic Infrared Small Target Detection via Zoom-Guided Interaction Learning

arXiv:2610.05342v1 Announce Type: new Abstract: Infrared small-target detection plays an important role in maritime monitoring and aerial surveillance. Although multimodal large language models (MLLMs

local-aiarxiv-cs-cv

MMLongCite: A Benchmark for Evaluating Faithfulness of Long-Context Vision-Language Models

arXiv:2510.13276v2 Announce Type: replace Abstract: The rapid advancement of long-context vision language models (LCVLMs) has led to a significant expansion of their context windows. However, an exten

Readout Blindness: VLM Scores Miss the Spatial Direction Their Frozen Encoders Retain

arXiv:2610.06324v1 Announce Type: new Abstract: CLIP-like vision-language models remain a cornerstone of multimodal systems, yet their scores stay near chance on directed spatial relations, such as wh

REFLEX: Reflective Evolution from LLM Experience

arXiv:2606.16496v2 Announce Type: replace-cross Abstract: Large multimodal language models (MLLMs) have emerged as powerful tools for guiding evolutionary search toward interpretable programmatic poli

researcharxiv-cs-lg

ReMAP: Restoring the Perceptual Cycle with Reasoning-Time Latent Visual Memory

arXiv:2610.05097v1 Announce Type: new Abstract: As multimodal large language models (MLLMs) reason for longer, attention to the initial visual input diminishes, weakening visual grounding. Visual memo

Scaling 3D Visual Grounding in Abdominal CT

arXiv:2610.04095v1 Announce Type: new Abstract: Visual grounding models can enhance radiology workflows by linking report findings to image regions. This is particularly valuable for 3D CT, where find

Score-Calibrated Flow for Sampling from Unnormalized Densities with Applications to Generative Online Reinforcement Learning

arXiv:2610.04696v1 Announce Type: new Abstract: Diffusion and flow models provide expressive policy classes for online reinforcement learning (RL), enabling multimodal behaviors and improved performan

Why Convolution Still Matters: Evaluating Inductive Biases in Cryospheric Image Classification

arXiv:2610.04073v1 Announce Type: new Abstract: Recent advances in attention-based deep learning have motivated their adoption for remote sensing image classification; however, their benefits for cryo

EviDent-CBCT: Evidence-Bottlenecked Report Generation from Dental CBCT under Non-Exhaustive Report Supervision

arXiv:2610.02375v1 Announce Type: cross Abstract: Dento-maxillofacial cone-beam CT (CBCT) reports may contain dozens of tooth-specific, anatomical, and spatial findings from a single 3D scan. Learning

local-aiarxiv-cs-ai

HyperFuse: Fast Self-Supervised Node Embeddings for Attributed Hypergraphs

arXiv:2610.03211v1 Announce Type: new Abstract: Self-supervised hypergraph representation learning can produce informative node embeddings, but existing methods often require deep encoders trained for

researcharxiv-cs-lg

NegT2IBench: When Negation Changes the Picture. A Polarity Benchmark for Text-to-Image Models

arXiv:2610.03084v1 Announce Type: cross Abstract: Text-to-image (T2I) models are judged by benchmarks that measure whether requested content appears, but these benchmarks largely overlook the compleme

Revealing Epistemic Uncertainty in MLLMs via Causal-Invariant Masking

arXiv:2610.02887v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) suffer from hallucinations, creating a critical need for Uncertainty Quantification (UQ) to ensure reliable d

THPL: A Vision-to-Language Decision Support Framework for Rainbow Trout Feeding Management in RAS

arXiv:2610.02378v1 Announce Type: new Abstract: In Recirculating Aquaculture Systems (RAS), precision feeding is critical for minimizing costs and improving fish welfare. However, existing methods lac

Continuous Conditioning of VLAs with Augmenting EMG and Visual Task Descriptors

arXiv:2610.01794v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models rely strongly on language for describing task information, despite having multimodal inputs. We hypothesize that oth

FORTE: Adaptive Scoring and Exact Keyframe Selection for Long-Video Question Answering

arXiv:2610.00573v1 Announce Type: new Abstract: Query-aware keyframe selection enables multimodal large language models (MLLMs) to process long videos using only a small set of question-relevant frame

Omni-Embed-Mini: Binding Modalities Without Forgetting via Dense Distillation

arXiv:2610.02148v1 Announce Type: new Abstract: Extending a text embedding model to new modalities typically degrades text retrieval quality, and existing omni-modal embedders compensate with multi-bi

The Geometry of Contextual Relations: Language Models Address Facts by Order of Mention

arXiv:2610.00910v1 Announce Type: cross Abstract: Human reasoning depends on how objects are related within propositions. extit{How do relations organize the language representations of contextual con

Agentic Tool-Augmented Reasoning for Explainable Image Forgery Detection

arXiv:2609.39066v1 Announce Type: new Abstract: Conventional image forgery detection methods produce binary scores or pixel-level masks without interpretable evidence, while recent multimodal large la

local-aiarxiv-cs-cv

Behavior-Grounded Semantic Enrichment for Financial Fraud Modeling and Reasoning

arXiv:2609.34211v2 Announce Type: replace Abstract: In financial fraud detection, rich semantic context can provide important evidence for transaction behavior modeling and fraud reasoning. However, p

Tutorials

ChronoGraph: Functional 4D Scene Graphs with Vision-Language Models for Interaction Understanding and Grounded Planning

arXiv:2609.39665v1 Announce Type: new Abstract: Embodied agents must determine where to act, anticipate the resulting scene changes, and interpret observed outcomes to guide subsequent actions. This r

tutorialsarxiv-cs-ai

Diffusion-2BC: Hybrid Diffusion and Regression Training for Offline Behavior Cloning in Autonomous Driving

model-releasesarxiv-cs-lg

arXiv:2609.38472v1 Announce Type: cross Abstract: Behavior cloning provides an offline route to autonomous-driving policy learning, but mean-squared-error regression is poorly matched to demonstration

EgoTools: Towards Tool-Centric Reasoning in Real-World Egocentric Videos

arXiv:2609.39378v1 Announce Type: new Abstract: Real-world embodied tasks, from everyday activities to professional procedures, require agents to act under physical constraints while tracking evolving

FoCLIP: A Feature-Space Misalignment Framework for CLIP-Based Image Manipulation and Detection

arXiv:2511.06947v2 Announce Type: replace-cross Abstract: The well-aligned attribute of CLIP-based models enables its effective application like CLIPscore as a widely adopted image quality assessment

From Given to Gathered Evidence: Agentic Learning for Longitudinal Medical Reasoning

arXiv:2609.39566v1 Announce Type: new Abstract: Foundation models can serve as clinical agents through tool-use harnesses. However, conventional medical benchmarks assess reasoning over preselected ev

LEARN-TS: LLM-Enhanced Alignment and Reconstruction with Normality Guidance for Multivariate Time-Series Anomaly Detection

arXiv:2609.38789v1 Announce Type: new Abstract: Reconstruction errors in multivariate time-series anomaly detection may not reliably distinguish abnormal behavior from benign deviations. Language-deri

Learning to Explain While Planning: Rule-Aligned Diffusion Planning for Autonomous Driving

arXiv:2609.39995v1 Announce Type: new Abstract: Diffusion planners exhibit strong capabilities in generating multimodal trajectories. However, existing methods primarily rely on expert demonstrations

LoopVL: Recurrent Visual Intelligence

arXiv:2609.38426v1 Announce Type: cross Abstract: We introduce LoopVL to study whether Loop Transformers can be effectively extended to vision- language models. LoopVL combines Module-Loop and Model-L

researcharxiv-cs-cl

A Skill-augmented Agentic Framework and Benchmark for Multi-Video Understanding

arXiv:2603.14733v2 Announce Type: replace Abstract: Multimodal Large Language Models have achieved strong performance in single-video understanding, yet their ability to reason across multiple videos

COMiT: Learning Structured Visual Tokens through Sequential Communication

arXiv:2602.20731v2 Announce Type: replace-cross Abstract: Discrete image tokenizers provide a sequential interface for vision and multimodal models, but are typically optimized for reconstruction or c

Decoding Affective Nuances: Enhancing MLLMs via Hierarchical Emotion Reasoning and Contrastive Discriminative Pruning

arXiv:2609.36782v1 Announce Type: new Abstract: While multimodal large language models (MLLMs) have demonstrated exceptional capabilities in objective understanding tasks, their performance in affecti

Applications

Devils in Question Relay: Source-Conditioned Relay Steering to Mitigate Hallucinations in Audio-visual Large Language Models

arXiv:2609.37568v1 Announce Type: new Abstract: Audio-visual large language models (AVLLMs) have made remarkable progress in multimodal understanding and reasoning through interactions among visual, a

applicationsarxiv-cs-cl

Agents

Exemplar2VQA: A Scalable Exemplar-Driven Visual Question Answering Generation Framework via Multi-Agent Coding

arXiv:2609.37655v1 Announce Type: new Abstract: Advancing spatial intelligence in Multimodal Large Language Models (MLLMs) is bottlenecked by the scarcity of complex, scalable 3D question-answer (QA)

agentsarxiv-cs-cv

FORUM: Frozen Outputs Reconciled Using Model Agreement for Visual Grounding

model-releasesarxiv-cs-cl

arXiv:2609.37488v1 Announce Type: cross Abstract: Frozen multimodal large language models (MLLMs) now solve standard referring expression comprehension with a single prompted call, yet on adversarial

Imagine3D-LLM: Teaching MLLMs to Imagine 3D Scenes Before Answering

arXiv:2609.38177v1 Announce Type: cross Abstract: Reasoning about the 3D world from multi-view images remains a fundamental challenge for Multimodal Large Language Models (MLLMs). While modern MLLMs h

researcharxiv-cs-cl

Tutorials

Iterative Exact Discrete Guidance for Energy-Based Sampling

arXiv:2609.37043v1 Announce Type: new Abstract: Sampling from unnormalized distributions over large discrete state spaces becomes difficult when a multimodal target is far from a tractable reference.

tutorialsarxiv-cs-lg

Agents

Multi-Agent Flow Matching with Decoupled Generative Guidance

arXiv:2609.38133v1 Announce Type: cross Abstract: Generative modeling is widely used for producing diverse objects from complex, multimodal distributions. However, its expressivity does not, in genera

agentsarxiv-cs-ro

OmniRoute: Mapping Temporal Semantic Evidence to Audio-Visual Token Budgets for Efficient Omnimodal Large Language Models

arXiv:2609.37052v1 Announce Type: new Abstract: Omnimodal large language models (Omni-LLMs) encode audio and visual streams into temporally interleaved token sequences for multimodal reasoning. Howeve

Representation Dynamics Reveal Semantic Saliency and Similarity for Visual Token Pruning in MLLMs

arXiv:2609.36916v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) incur high inference latency from long visual token sequences. Existing pruning methods commonly use attention

SAM Meets VLM: Parameter-Decoupled Full-Parameter Training for Unified Medical Reasoning and Segmentation

arXiv:2609.37283v1 Announce Type: new Abstract: Medical multimodal large language models (MLLMs) are increasingly expected not only to answer clinical questions, but also to localize the visual eviden

Selective Channel Restoration for Backdoored Vision-Language Models

arXiv:2609.37759v1 Announce Type: cross Abstract: Vision-language models (VLMs) exhibit strong multimodal capabilities but remain vulnerable to backdoors implanted through poisoned fine-tuning data. E

VIF-Bench: Evaluating Visual Instruction Following in Multi-Reference Image Generation

arXiv:2609.37709v1 Announce Type: cross Abstract: Recent multimodal image generation models can take multiple images and textual instructions as input, enabling reference-based generation guided not o

Visual Parallel Search: Learning to Search High-Resolution Images with Parallel Tile Inspection and Adaptive Zoom

arXiv:2609.37002v1 Announce Type: cross Abstract: High-resolution visual question answering often fails because a multimodal model does not acquire the small, spatially localized evidence needed to an