Search: “multimodal”

Divide and Conquer: Mixture-of-Bottleneck Experts in Informative Ordinal Space for Video-based Multimodal Sentiment Analysis

arXiv:2609.18470v1 Announce Type: cross Abstract: Video-based Multimodal sentiment analysis (MSA) must handle information from text, audio, and image sequence in human speaking videos, yet current met

researcharxiv-cs-cl

17 Sept 2026

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Model Releases

V-ICAL Bench: Evaluating Video In-Context Learning for Multimodal Agents in Interactive Environments

DGX agent

arXiv:2609.15683v1 Announce Type: new Abstract: While In-Context Learning (ICL) enables models to adapt from exemplars without parameter updates, multimodal ICL remains largely underexplored, particul

model-releasesarxiv-cs-cv

15 Sept 2026

Mr.LHDR: A Benchmark for Multimodal Real-World Long-Horizon Deep Research Agents

arXiv:2609.11318v1 Announce Type: new Abstract: Deep research agents are increasingly capable of web search, tool use, multimodal evidence analysis, and information synthesis. However, existing benchm

12 Sept 2026

SGM: Safety Glasses for Multimodal Large Language Models via Neuron-Level Detoxification

arXiv:2512.15052v4 Announce Type: replace-cross Abstract: Disclaimer: Samples in this paper may be harmful and cause discomfort. Multimodal large language models (MLLMs) enable multimodal understandin

1 Sept 2026

TAMI: Temporally Aligned, Missingness-Aware, and Interpretable Multimodal Fusion for Mental Health Assessment in Older Adults with Mild Cognitive Impairment

arXiv:2608.30857v1 Announce Type: cross Abstract: Depression and anxiety in older adults with Mild Cognitive Impairment (MCI) are frequently underdiagnosed due to limited access to care. Multimodal an

1 Sept 2026

ReCoG: Reciprocal Co-Evolution for Multimodal Graph Learning

arXiv:2608.22786v1 Announce Type: new Abstract: Multimodal graph learning requires jointly training over graph structure and heterogeneous node attributes, yet existing methods largely decouple these

researcharxiv-cs-lg

25 Aug 2026

Tutorials

Decoupled Vision-Language System for Multimodal Understanding and Generation

arXiv:2608.20382v1 Announce Type: new Abstract: We introduce a new architecture design for multimodal large language models (MLLMs), Libra, capable of both multimodal understanding and generation. Lib

tutorialsarxiv-cs-cl

Interpretable Multimodal Classification with Linear Discriminant Tree Ensembles

arXiv:2608.20384v1 Announce Type: new Abstract: Multimodal affect and behaviour classifiers that fuse heterogeneous text, audio, and visual streams must simultaneously achieve competitive accuracy and

SuppreSensing: Expert-Guided Feature Recalibration and Discrepancy Augmentation for Multimodal Object Detection

arXiv:2608.20944v1 Announce Type: new Abstract: Multimodal object detection in remote sensing faces challenges due to semantic heterogeneity and modality-specific noise interference. To this end, we p

MedUAG: Unified Understanding and Generation for Medical Multimodal Models

arXiv:2608.18937v1 Announce Type: cross Abstract: Recent Multimodal Large Language Models (MLLMs) are rapidly evolving into unified understanding and generation (UAG) frameworks. However, extending th

20 Aug 2026

CASA: Classification Augmented with Safety Attention for Robust Multimodal Alignment

arXiv:2604.00310v2 Announce Type: replace-cross Abstract: Multimodal large-language models (MLLMs) often experience degraded safety alignment when harmful queries exploit cross-modal interactions. Mod

10 Aug 2026

Illuminating Visual Identity in Universal Multimodal Embeddings

model-releasesarxiv-cs-cl

arXiv:2608.01794v1 Announce Type: cross Abstract: Universal Multimodal Embeddings (UMEs) aim to unify various modalities and tasks into a shared representation space. In recent years, this field has w

4 Aug 2026

StanceFlip: A Comprehensive Multi-Dimensional Benchmark for Multimodal Conversational Stance Flipping Forecasting

arXiv:2607.24191v1 Announce Type: cross Abstract: Conversational stance detection has shifted from static text analysis to dynamic multimodal modeling. However, existing benchmarks exhibit three key l

28 Jul 2026

Scaling Native Multimodal Pre-Training From Scratch

arXiv:2607.22043v1 Announce Type: new Abstract: Although large language models (LLMs) exhibit remarkable reasoning capabilities, their reliance on text-only pre-training restricts the perception of th

researcharxiv-cs-cl

27 Jul 2026

Attention Misses Visual Risk: Risk-Adaptive Steering for Multimodal Safety Alignment

arXiv:2510.13698v4 Announce Type: replace Abstract: Even modern AI models often remain vulnerable to multimodal queries in which harmful intent is embedded in images. A widely used approach for safety

15 Jul 2026

Do We Really Need Multimodal Emotion Language Models Larger Than 1B Parameters?

arXiv:2607.12787v1 Announce Type: new Abstract: Recent advances in multimodal large language models (MLLMs) have significantly improved the performance of multimodal emotion recognition (MER) and enab

15 Jul 2026

DeltaV: Thinking with Visual State Updates in Unified Large Multimodal Models

arXiv:2607.08434v1 Announce Type: new Abstract: Current Unified Large Multimodal Models (ULMMs) support interleaved multimodal reasoning through textual reasoning and intermediate visual states, but t

10 Jul 2026

DMC-CF: Dynamic Multimodal CounterFactual QA benchmark for Causal Reasoning

arXiv:2605.29339v1 Announce Type: new Abstract: With the rapid advancement of multimodal large language models (MLLMs), models have demonstrated increasingly powerful multimodal capabilities. However,

29 May 2026

MULTISEISMO: A Multimodal Seismic Dataset and Model for Cross-Modal Seismic Understanding

model-releasesarxiv-cs-cl

arXiv:2605.26320v1 Announce Type: cross Abstract: The application of generalist multimodal models (GMMs) to specialized scientific domains remains limited due to the scarcity of comprehensive domain-s

27 May 2026

Beyond Accuracy: Benchmarking Cross-Task Consistency in Unified Multimodal Models

arXiv:2604.25072v1 Announce Type: new Abstract: Unified Multimodal Models (uMMs) aim to support both visual understanding and visual generation within a shared representation. However, existing evalua

29 Apr 2026

mKG-RAG: Leveraging Multimodal Knowledge Graphs in Retrieval-Augmented Generation for Knowledge-intensive VQA

arXiv:2508.05318v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has emerged as an effective paradigm for expanding the knowledge capacity of Multimodal Large Language Mo

28 Apr 2026

Tuna-2: Pixel Embeddings Beat Vision Encoders for Multimodal Understanding and Generation

arXiv:2604.24763v1 Announce Type: new Abstract: Unified multimodal models typically rely on pretrained vision encoders and use separate visual representations for understanding and generation, creatin

28 Apr 2026

Compose and Fuse: Revisiting the Foundational Bottlenecks in Multimodal Reasoning

arXiv:2509.23744v3 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) promise enhanced reasoning by integrating diverse inputs such as text, vision, and audio. Yet cross-m

24 Apr 2026

Learning Dynamic Representations and Policies from Multimodal Clinical Time-Series with Informative Missingness

arXiv:2604.21235v1 Announce Type: cross Abstract: Multimodal clinical records contain structured measurements and clinical notes recorded over time, offering rich temporal information about the evolut

safetyarxiv-cs-cl

24 Apr 2026

Perception-Aware Policy Optimization for Multimodal Reasoning

arXiv:2507.06448v5 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has proven to be a highly effective strategy for endowing Large Language Models (LLMs) with ro

safetyarxiv-cs-cl

15 Apr 2026

Bottleneck Tokens for Unified Multimodal Retrieval

arXiv:2604.11095v1 Announce Type: cross Abstract: Adapting decoder-only multimodal large language models (MLLMs) for unified multimodal retrieval faces two structural gaps. First, existing methods rel

14 Apr 2026

MMR-AD: A Large-Scale Multimodal Dataset for Benchmarking General Anomaly Detection with Multimodal Large Language Models

arXiv:2604.10971v1 Announce Type: cross Abstract: In the progress of industrial anomaly detection, general anomaly detection (GAD) is an emerging trend and also the ultimate goal. Unlike the conventio

14 Apr 2026

OpenVLThinkerV2: A Generalist Multimodal Reasoning Model for Multi-domain Visual Tasks

arXiv:2604.08539v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) has emerged as the de facto Reinforcement Learning (RL) objective driving recent advancements in Multimodal

safetyarxiv-cs-cl

10 Apr 2026

PLUME: Latent Reasoning Based Universal Multimodal Embedding

arXiv:2604.02073v2 Announce Type: replace Abstract: Universal multimodal embedding (UME) maps heterogeneous inputs into a shared retrieval space with a single model. Recent approaches improve UME by g

10 Apr 2026

Aligning Multimodal Patient Evidence with Biomedical Knowledge Graphs for Clinical LLMs

arXiv:2610.06685v1 Announce Type: new Abstract: Clinical questions often depend on linking a patient's multimodal evidence to external biomedical knowledge, yet existing predictive systems rarely repr

safetyarxiv-cs-lg

6 Oct 2026

DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Experts

arXiv:2412.10510v5 Announce Type: replace Abstract: The proliferation of disinformation demands reliable and scalable fact-checking solutions. We present Dynamic Evidence-based FAct-checking with Mult

6 Oct 2026

Long-MDR: Long-Context Reinforcement Learning for Multimodal Deep-Research Agents

arXiv:2610.05195v1 Announce Type: new Abstract: The next generation of multimodal research agents must reason over long-lived research histories rather than short model completions. During a single ta

6 Oct 2026

Balancing Multimodal Learning via Functional Progress

arXiv:2610.03035v1 Announce Type: new Abstract: Multimodal learning often suffers from modality imbalance, where the joint optimization process is dominated by a single modality. Existing methods typi

researcharxiv-cs-lg

5 Oct 2026

Tutorials

No-Free-Graph: Learning When Multimodal Data Should Be Graphified

arXiv:2610.02768v1 Announce Type: new Abstract: Multimodal graph learning has recently emerged as an effective paradigm for in corporating inter-entity relationships into multimodal representations. E

tutorialsarxiv-cs-lg

5 Oct 2026

A Low Grounding Score Is Not an Ungrounded Judge: Identifying the Perceptibility Confound in Multimodal Oversight

arXiv:2610.00111v1 Announce Type: new Abstract: Model judges now supervise multimodal systems at scale, filtering training data, selecting outputs, and supplying the reward that shapes multimodal reas

2 Oct 2026

MMMG: a Comprehensive and Reliable Benchmark for Multitask Multimodal Generation

arXiv:2505.17613v2 Announce Type: replace Abstract: Automatically evaluating multimodal generation presents a significant challenge, as automated metrics often struggle to align with human evaluation,

2 Oct 2026

Tutorials

QiYao-M: Multimodal Time Series Foundation Model with Role-Aware Modeling of Endogenous and Exogenous Modalities

arXiv:2609.34842v1 Announce Type: new Abstract: Existing multimodal time series foundation models (TSFMs) typically model heterogeneous modalities through largely shared mechanisms, overlooking the di

tutorialsarxiv-cs-lg

29 Sept 2026

Agents

MedTRACE: Tool-Augmented Multimodal Clinical Reasoning Agents for Evidence-Grounded Decision-Making

arXiv:2609.14823v1 Announce Type: new Abstract: Multimodal clinical decision-making requires reliable reasoning over heterogeneous evidence from electronic health records, medical images, and physiolo

agentsarxiv-cs-cl

15 Sept 2026

CrossModalQA: A Cross-modal and Multi-hop Benchmark for Multimodal Retrieval-augmented Generation

arXiv:2609.05518v1 Announce Type: new Abstract: Despite the strong capabilities of multimodal large language models (MLLMs), their parametric knowledge remains incomplete and difficult to update, moti

9 Sept 2026

Dreaming in Flow: Generative Grounding Feedback for Self-Evolving Unified Multimodal Models

arXiv:2609.08282v1 Announce Type: new Abstract: Unified multimodal models integrate visual understanding and generation within a single network, yet the two capabilities are commonly optimized as sepa

9 Sept 2026

Do Multimodal LLMs See Before They Read? Diagnosing Contextual Sycophancy

arXiv:2609.00067v1 Announce Type: cross Abstract: External text can override conflicting image evidence in multimodal large language models, a failure we call multimodal contextual sycophancy. We intr

2 Sept 2026

EM^2Mem: Event-Centric Multimodal Memory for Large Language Models

arXiv:2609.00551v1 Announce Type: cross Abstract: Multimodal memory offers a scalable interface for long-video question answering, but existing methods often retrieve captions, frames, transcripts, su

2 Sept 2026

Applications

Modality Disentangled Learning for Incomplete Multimodal Emotion Recognition: A Primitive Memory Distillation Perspective

arXiv:2608.30563v1 Announce Type: new Abstract: Multimodal Emotion Recognition (MER) systems often suffer from missing modalities in real-world scenarios. Existing methods usually generate, align, or

applicationsarxiv-cs-cv

1 Sept 2026

Recurrence Meets Transformers for Universal Multimodal Retrieval

arXiv:2509.08897v2 Announce Type: replace-cross Abstract: With the rapid advancement of multimodal retrieval and its application in LLMs and multimodal LLMs, increasingly complex retrieval tasks have

researcharxiv-cs-cl

27 Aug 2026

Local Ai

ReFrame: Evidence-Guided Test-Time Safety Alignment in Multimodal Large Language Models

arXiv:2608.21100v1 Announce Type: new Abstract: While multimodal large language models (MLLMs) extend model capabilities beyond text, they also make safety alignment increasingly challenging. Multimod

local-aiarxiv-cs-ai

COMIC: Reference-Aware Safety Gating for Multimodal Large Language Models

arXiv:2608.17234v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are increasingly used to interact with screenshots, scanned documents, diagrams, and other visually grounded

19 Aug 2026

Which Modality Decides? Counterfactual Modality Attribution for Multimodal LLMs

arXiv:2608.00076v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) increasingly support high-stakes decision making by combining complementary information from images and text. W

4 Aug 2026

CAER: Conflict-Aware Evidence Routing with Dual Prefix Experts for Multimodal Large Language Models

arXiv:2607.28991v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in multimodal understanding and generation. However, when textual inp