Search: “multimodal”

MAP4TS: A Multi-Aspect Prompting Framework for Time-Series Forecasting with Large Language Models

model-releasesarxiv-cs-cl

arXiv:2510.23090v2 Announce Type: replace Abstract: Recent advances have investigated the use of pretrained large language models (LLMs) for time-series forecasting by aligning numerical inputs with L

22 May 2026

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Model Releases

Pre-VLA: Preemptive Runtime Verification for Reliable Vision-Language-Action and World-Model Rollouts

DGX agent

arXiv:2605.22446v1 Announce Type: new Abstract: While large vision-language-action (VLA) models and generative world models (WM) have advanced long-horizon embodied intelligence, their practical deplo

model-releasesarxiv-cs-cv

22 May 2026

SURGE: An Event-Centric Social Media Sentiment Time Series Benchmark with Interaction Structure

arXiv:2605.21198v1 Announce Type: cross Abstract: Public events on social media generate large volumes of discussion whose collective dynamics carry direct value for opinion forecasting and crisis res

22 May 2026

TextTeacher: What Can Language Teach About Images?

arXiv:2605.22098v1 Announce Type: new Abstract: The platonic representation hypothesis suggests that sufficiently large models converge to a shared representation geometry, even across modalities. Mot

tutorialsarxiv-cs-cv

22 May 2026

ClaimDiff-RL: Fine-Grained Caption Reinforcement Learning through Visual Claim Comparison

arXiv:2605.20278v1 Announce Type: cross Abstract: Long-form image captioning exposes a reward granularity problem in RL: captions are judged as whole sequences, while the important errors occur at the

Applications

Findings of the Counter Turing Test: AI-Generated Image Detection

arXiv:2605.20787v1 Announce Type: new Abstract: The rapid advancements in generative AI technologies, such as Stable Diffusion, DALL-E, and Midjourney, have significantly transformed the creation of s

applicationsarxiv-cs-cv

Applications

FruitEnsemble: MLLM-Guided Arbitration for Heterogeneous ensemble in Fine-Grained Fruit Recognition

arXiv:2605.20892v1 Announce Type: new Abstract: Fine-grained fruit classification is a critical yet challenging task in agricultural computer vision, primarily hindered by a severe shortage of high-qu

applicationsarxiv-cs-cv

FullFlow: Upgrading Text-to-Image Flow Matching Models for Bidirectional Vision--Language Generation

arXiv:2605.20316v1 Announce Type: new Abstract: Modern text-to-image diffusion models encode rich visual priors, but expose them only through one-way text-conditioned generation. Existing unified visi

Leveraging Vision-Language Models to Detect Attention in Educational Videos

arXiv:2605.20211v1 Announce Type: new Abstract: Educational videos are a cornerstone of remote and blended learning. However, learners' fluctuating attention remains a significant barrier to effective

Agents

MASFactory: A Graph-centric Framework for Orchestrating LLM-Based Multi-Agent Systems with Vibe Graphing

arXiv:2603.06007v2 Announce Type: replace Abstract: Large language model-based (LLM-based) multi-agent systems (MAS) are increasingly used to extend agentic problem solving via role specialization and

agentsarxiv-cs-cl

Agents

MC-Risk: Multi-Component Risk Fields for Risk Identification and Motion Planning

arXiv:2605.21406v1 Announce Type: new Abstract: We present MC-Risk, a planner-aligned, multi-component risk field on a bird's-eye-view grid that yields early, calibrated, and class-aware risk localiza

agentsarxiv-cs-ro

Local Ai

OSGNet with MLLM Reranking @ Ego4D Episodic Memory Challenge 2026

arXiv:2605.20818v1 Announce Type: new Abstract: In this report, we present our champion solutions for the Natural Language Queries and GoalStep tracks of the Ego4D Episodic Memory Challenge at CVPR 20

local-aiarxiv-cs-cv

Pareto-Enhanced Portrait Generation: Vision-Aligned Text Supervision for Alignment, Realism, and Aesthetics

arXiv:2605.20640v1 Announce Type: new Abstract: Text-to-image diffusion models often face a severe trilemma in human portrait generation: text-image alignment, photorealism, and human-perceived aesthe

ShadeBench: A Benchmark Dataset for Building Shade Simulation in Sustainable Society

arXiv:2605.20510v1 Announce Type: new Abstract: Urban heat exposure is becoming an increasingly critical challenge due to the intensifying urban heat island effect. Fine-grained shade patterns, especi

STiTch: Semantic Transition and Transportation in Collaboration for Training-Free Zero-Shot Composed Image Retrieval

arXiv:2605.21261v1 Announce Type: new Abstract: Training-free zero-shot composed image retrieval models are recently gaining increasing research interest due to their generalizability and flexibility

The Visual Iconicity Challenge: Evaluating Vision-Language Models on Sign Language Form-Meaning Mapping

model-releasesarxiv-cs-cl

arXiv:2510.08482v3 Announce Type: replace-cross Abstract: Iconicity, the resemblance between linguistic form and meaning, is pervasive in signed languages, offering a natural testbed for visual ground

Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos

arXiv:2605.18984v1 Announce Type: new Abstract: Recent video generative models have greatly improved the realism of AI-generated videos, yet their outputs still exhibit artifacts such as temporal inco

Beyond Waypoints: Dual-Heatmap Grounding for Cross-Embodiment Semantic Navigation

model-releasesarxiv-cs-ro

arXiv:2605.19420v1 Announce Type: new Abstract: Grounding open-ended semantic instructions into physically executable local goals is a fundamental challenge in human-robot interaction. While existing

Brain alignment of reasoning and action representations from vision-language and action models during naturalistic gameplay

arXiv:2605.19352v1 Announce Type: cross Abstract: Understanding how humans and artificial intelligence systems predict and plan by interacting with their environment is a fundamental challenge at the

CEPO: RLVR Self-Distillation using Contrastive Evidence Policy Optimization

arXiv:2605.19436v1 Announce Type: cross Abstract: When a model produces a correct solution under reinforcement learning with verifiable rewards (RLVR), every token receives the same reward signal rega

safetyarxiv-cs-cl

Character-Centered Dialogue Generation from Scene-Level Prompts

arXiv:2505.16819v4 Announce Type: replace Abstract: Recent advances in scene-based video generation enable coherent visual narratives from structured prompts, yet a key aspect of storytelling -- chara

tutorialsarxiv-cs-cv

CLIC: Contextual Language-Informed Cardiac Pathology Classification

arXiv:2605.19132v1 Announce Type: new Abstract: The electrocardiogram (ECG) is the gold standard for non-invasive diagnosis of cardiac pathologies and is a fundamental pillar of cardiovascular medicin

researcharxiv-cs-lg

Diffusion and Flow-based Copulas: Forgetting and Remembering Dependencies

arXiv:2509.19707v2 Announce Type: replace-cross Abstract: Copulas are a fundamental tool for modelling multivariate dependencies in data, forming the method of choice in diverse fields and application

tutorialsarxiv-cs-lg

Dynamic Model Merging Made Slim

arXiv:2605.18904v1 Announce Type: cross Abstract: Model merging enables the reuse of fine-tuned models without joint training or access to original data. Dynamic merging further improves flexibility b

Efficient Long-Context Modeling in Diffusion Language Models via Block Approximate Sparse Attention

arXiv:2605.19726v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) enable globally coherent, bidirectional, and controllable text generation, offering advantages over traditional autoreg

researcharxiv-cs-cv

Efficient Transferable Optimal Transport via Min-Sliced Transport Plans

arXiv:2511.19741v3 Announce Type: replace Abstract: Optimal Transport (OT) offers a powerful framework for finding correspondences between distributions and addressing matching and alignment problems

EMO-BOOST: Emotion-Augmented Audio-Visual Features for Improved Generalization in Deepfake Detection

arXiv:2605.19630v1 Announce Type: new Abstract: With every advancement in generative AI models, forensics is under increasing pressure. The constant emergence of new generation techniques makes it imp

researcharxiv-cs-ai

Feature-Space Smoothing: Certified Robustness of Deep Representations

arXiv:2601.16200v3 Announce Type: replace-cross Abstract: Modern deep learning models exhibit strong capabilities across diverse applications, yet remain vulnerable to malicious inputs that induce err

From Prompts to Pavement Through Time: Temporal Grounding in Agentic Scene-to-Plan Reasoning

arXiv:2605.19824v1 Announce Type: new Abstract: Recent attempts to support high-level scene interpretation and planning in Autonomous Vehicles (AVs) using ensembles of Large Language Models (LLMs) and

GeoX: Mastering Geospatial Reasoning Through Self-Play and Verifiable Rewards

arXiv:2605.20006v1 Announce Type: new Abstract: Geospatial reasoning requires solving image-grounded problems over the complex spatial structure of a scene. However, developing this capability is hind

Governing Evolving Memory in LLM Agents: Risks, Mechanisms, and the Stability and Safety Governed Memory (SSGM) Framework

arXiv:2603.11768v2 Announce Type: replace Abstract: Long-term memory has emerged as a foundational component of autonomous Large Language Model (LLM) agents, enabling continuous adaptation, lifelong m

Local Ai

iDiff: Interpretable Difference-aware Framework for Pairwise Image Quality Assessment

arXiv:2605.19522v1 Announce Type: new Abstract: Pairwise image quality assessment (IQA) in professional photography requires a model not only to identify the preferred image between two candidates, bu

local-aiarxiv-cs-cv

INAR-VL: Input-Aware Routing for Edge-Cloud Vision-Language Inference

arXiv:2605.18853v1 Announce Type: cross Abstract: Edge deployment of Vision-Language Models (VLMs) faces a tradeoff between latency and accuracy: cloud execution provides high-quality predictions but

tutorialsarxiv-cs-cv

MSAlign: Aligning Molecule and Mass Spectra Foundation Models for Metabolite Identification

model-releasesarxiv-cs-lg

arXiv:2605.19752v1 Announce Type: new Abstract: Accurately identifying metabolites i.e. small molecules from mass spectrometry data remains a core challenge in metabolomics, with broad applications in

Not Every Rubric Teaches Equally: Policy-Aware Rubric Rewards for RLVR

arXiv:2605.20164v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards has made post-training highly effective when correctness can be checked automatically. However, many impo

PixVerve: Advancing Native UHR Image Generation to 100MP with a Large-Scale High-Quality Dataset

arXiv:2605.20147v1 Announce Type: new Abstract: Text-to-Image (T2I) models have recently seen notable progress around 1K and 2K resolution. With the extreme desire for better visual experience and the

Proximal Diffusion Neural Sampler

arXiv:2510.03824v2 Announce Type: replace-cross Abstract: The task of learning a diffusion-based neural sampler for drawing samples from an unnormalized target distribution can be viewed as a stochast

researcharxiv-cs-ai

SimGym: A Framework for A/B Test Simulation in E-Commerce with Traffic-Grounded VLM Agents

arXiv:2605.19219v1 Announce Type: new Abstract: A/B testing remains the gold standard for evaluating modifications to e-commerce storefronts, yet it diverts traffic, requires weeks to reach statistica

SpecX: A Large-Scale Benchmark for Multi-Modal Spectroscopy and Cross-Paradigm Evaluation

arXiv:2605.18791v1 Announce Type: cross Abstract: Existing spectral benchmarks are limited in scale, modality alignment, and evaluation scope, and typically focus on either specialized models or multi

SynGR: Unleashing the Potential of Cross-Modal Synergy for Generative Recommendation

arXiv:2605.18920v1 Announce Type: cross Abstract: Generative Recommendation (GR) has emerged as a promising paradigm by formulating item recommendation as a sequence-to-sequence generation task over i

WARC-Bench: Web Archive Based Benchmark for GUI Subtask Executions

arXiv:2510.09872v2 Announce Type: replace-cross Abstract: Training web agents to navigate complex, real-world websites requires them to master extit{subtasks} - short-horizon interactions on multiple

A Unified Framework for Data-Free One-Step Sampling via Wasserstein Gradient Flows

arXiv:2605.17808v1 Announce Type: new Abstract: We develop a unified theoretical framework for data-free one-step sampling from unnormalized target distributions based on Wasserstein gradient flows. F

researcharxiv-cs-lg

Advancing Narrative Long Video Generation via Training-Free Identity-Aware Memory

arXiv:2605.18733v1 Announce Type: new Abstract: Autoregressive video generation has improved rapidly in visual fidelity and interactivity, but it still suffers from long-term inconsistency and memory

Agents

Agentic Pipeline for Self-Synchronized Multiview Joint Angle Monitoring in Uncalibrated Environments

arXiv:2605.16419v1 Announce Type: cross Abstract: Kinematic monitoring plays a critical role in long-term rehabilitation for patients with spinal cord injury (SCI), where multi-view markerless motion

agentsarxiv-cs-ai

AI Slop or AI-enhancement? Student perceptions of AI-generated media for an English for Academic Purposes course

arXiv:2605.16275v1 Announce Type: cross Abstract: Artificial intelligence (AI) retrieval-augmented generation (RAG) tools now enable educators to transform course materials into diverse multimedia at

tutorialsarxiv-cs-ai

Breaking Annotation Barriers: Generalized Video Quality Assessment via Ranking-based Self-Supervision

arXiv:2505.03631v4 Announce Type: replace Abstract: Video quality assessment (VQA) is essential for quantifying perceptual quality in various video processing workflows, spanning from camera capture s

Code as Agent Harness

arXiv:2605.18747v1 Announce Type: cross Abstract: Recent large language models (LLMs) have demonstrated strong capabilities in understanding and generating code, from competitive programming to reposi

CT-DegradBench: A Physics-Informed Benchmark for CT Degradation Detection and Severity Estimation

arXiv:2605.16431v1 Announce Type: new Abstract: Computed tomography (CT) images are frequently degraded by acquisition artifacts, including noise, blur, streaking, aliasing, and metal artifacts. Yet C