Search: “multimodal”

PunGraph: Retrieval-Enhanced Phonetic-Semantic Graph Reasoning for Pun Understanding

arXiv:2609.16557v1 Announce Type: new Abstract: Puns are a challenging form of figurative language that exploit phonetic similarity and semantic ambiguity to convey multiple meanings. Although large l

researcharxiv-cs-cl

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

SceneBench: A Hierarchical Benchmark for Vision-Language Understanding of 3D Scenes

DGX agent

arXiv:2609.16233v1 Announce Type: cross Abstract: Vision-language models excel at 2D image understanding but remain limited in 3D spatial reasoning. Progress is hindered by limitations in current benc

model-releasesarxiv-cs-ai

16 Sept 2026

Sparse MLLM Anchors, Dense Adaptation: Breaking the Self-Referential Loop in Wild Test-Time Adaptation

arXiv:2609.17040v1 Announce Type: new Abstract: Wild test-time adaptation (WTTA) updates a source model online under small test batches, concurrent distribution shifts, and time-varying class imbalanc

SPEAR NeXT Causal Latent Forecasting Across Multiple Horizons for Spectral Temporal Earth Representation Learning

arXiv:2609.16871v1 Announce Type: new Abstract: Earth observation is inherently dynamic, yet temporal information in many foundation models is learned through reconstruction, invariance, or retrospect

TEDi: Temporal Memory-Enhanced and Denoising Transformer for Surgical Instrument Segmentation

arXiv:2609.16797v1 Announce Type: new Abstract: Query-based segmentation methods have shown promising potential for surgical instrument segmentation and recognition, which is essential for scene under

3D Gait-Based Autism Classification Using Attention-Enhanced Deep Learning with Cross-Fold Statistical Stability Analysis

arXiv:2609.14159v1 Announce Type: new Abstract: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition whose early diagnosis remains challenging because conventional clinical assessments are

An Incomplete Loop: Deductive, Inductive, and Abductive Reasoning in Language Models

arXiv:2404.03028v4 Announce Type: replace Abstract: Modern language models (LMs) can learn to perform new tasks in different ways: in instruction following, the target task is described explicitly in

Bellman Policy Optimization

arXiv:2609.15987v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) improves the reasoning capabilities of large language models (LLMs). We introduce Bellman Policy

safetyarxiv-cs-cl

Bench2Dex: Benchmarking Visuo-Tactile Bimanual Dexterous Manipulation Across Dexterous Hands

arXiv:2609.15726v1 Announce Type: cross Abstract: Tactile sensing provides contact information that can be difficult to infer from vision alone, but tactile hardware for dexterous hands has not conver

Beyond Accuracy: Robustness, Cost, and Governance Trade-offs for Vision-Language Models in Templated Document Extraction

arXiv:2609.15706v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly used to extract structured fields from business documents, yet most evaluations report accuracy on clean

Bridging the Modality Gap in Long-Form Clinical Audio: A Comparative Study of Lightweight and Heavyweight End-to-End SOAP Generation

arXiv:2609.14467v1 Announce Type: cross Abstract: Automating clinical documentation from long-form doctor-patient conversations remains challenging for modern audio-language models. While cascaded ASR

researcharxiv-cs-ai

CITECHOICE: A Causal Audit of How Document Presentation Redistributes Citation Credit in Agentic Search

arXiv:2609.15164v1 Announce Type: new Abstract: When several retrieved sources support the same claim, an answer engine cites some but not others. We call this decision citation allocation and introdu

agentsarxiv-cs-cl

Clinical Reasoning Under a Partially Observed Objective in Cone Beam CT Report Generation

arXiv:2609.13238v1 Announce Type: new Abstract: Maxillofacial report generation from cone beam computed tomography is scored here by a composite objective placing 80% of its weight on a large language

Convergent Emergence of In-Context Learning Across Modalities

arXiv:2609.14011v1 Announce Type: new Abstract: Few-shot in-context learning (ICL), the capacity of a model to infer abstract patterns from input-output examples provided in its prompt and apply them

researcharxiv-cs-ai

Diagnosing Temporal Misalignment in Multichannel Time-Series Classification with Minimum Description Length

arXiv:2609.14595v1 Announce Type: cross Abstract: Multichannel time-series classification commonly assumes synchronized sensor streams, although latency, clock drift, and preprocessing can introduce r

safetyarxiv-cs-ai

Local Ai

Don't Send What You Don't Need: Question-Guided Token Pruning as a Privacy Defense for Vision-Language Models

arXiv:2609.15671v1 Announce Type: cross Abstract: Visual Question Answering (VQA) with Vision-Language Models (VLMs) is increasingly used in privacy-sensitive and bandwidth-constrained settings. Feder

local-aiarxiv-cs-ai

Empirical Evaluation of Open-Source Large Language Models for Retrieval-Augmented Generation in ESG Domain

arXiv:2609.15242v1 Announce Type: new Abstract: Environmental, Social, and Governance (ESG) reporting is critical for corporate accountability, with Large Language Models (LLMs) and Retrieval-Augmente

ESAFusion: LiDAR--4-D Radar Fusion via Local Geometric Complementation and Multiscale Adaptive Interaction for 3-D Object Detection

arXiv:2609.14619v1 Announce Type: new Abstract: LiDAR--4-D radar fusion combines accurate spatial geometry with motion and reflectivity cues from radar, offering a promising solution for 3-D object de

From Semantic to Token Communication: The Next Paradigm for Large-Model-Driven 6G Intelligent Connectivity

arXiv:2609.10714v1 Announce Type: cross Abstract: The ambitious requirements of sixth-generation (6G) networks are driving communication systems from reliable bit delivery toward meaning-aware and tas

agentsarxiv-cs-ai

GRIN+: Towards Fast Yet Effective Machine Unlearning for Imbalanced Medical Data

arXiv:2609.15571v1 Announce Type: new Abstract: As deep learning models become fundamental to modern healthcare, the 'Right to be Forgotten' mandated by privacy regulations like GDPR and HIPAA necessi

Language-Guided Representation Learning for Robust Cross-Sensor Material Recognition

arXiv:2609.14783v1 Announce Type: cross Abstract: Robots need touch to manipulate objects safely and reliably, as many properties, such as softness, texture, and contact stability, are hard to infer f

LPA-CWM: A Learned Physical Adjudicator for Motion Reasoning with Counterfactual World Models

arXiv:2609.14073v1 Announce Type: cross Abstract: Counterfactual world models (CWM) extract motion from pretrained video predictors by comparing factual and intervened predictions. However, responses

Mind2Cloud: EEG-to-Point Cloud Generation with Two-Granularity Diffusion Decoding

arXiv:2609.13991v1 Announce Type: new Abstract: Reconstructing 3D objects from brain signals offers a promising avenue for understanding human visual cognition. While prior work has shown initial succ

NoteVQA: Benchmarking VLMs on Real-Life Questions from Human Communities

arXiv:2609.15695v1 Announce Type: new Abstract: Vision-language models (VLMs) increasingly power consumer-facing AI search, yet evaluating them on the diversity of everyday visual questions remains ch

agentsarxiv-cs-ai

Perceive, Refine, Reason: A Calibrated Pipeline for Measuring Indicators in Strategic Visual Communication on Social Media

arXiv:2609.14699v1 Announce Type: new Abstract: Visual content shapes audience perception and opinion on social media, and computational social science increasingly relies on automated tools to analyz

Tutorials

ProtoCAM: Interpretable Few-Shot Mask-Guided Prototypical Learning for Breast Lesion Classification in Ultrasound Imaging

arXiv:2609.13340v1 Announce Type: cross Abstract: Breast ultrasound imaging plays an important role in the early detection and diagnosis of breast cancer, particularly for patients with dense breast t

tutorialsarxiv-cs-ai

Quantum-Gated LiteSSD: A Parameter-Efficient Lightweight Hybrid Quantum-Classical Framework for Forward-Looking Sonar Object Detection

arXiv:2609.14025v1 Announce Type: new Abstract: Forward-looking sonar object detection is essential for underwater perception, yet deployment on embedded platforms requires highly compact models. To a

RA-CoA: Training-free Fashion Image Captioning via Retrieval-Augmented Chain-of-Attributes

arXiv:2609.14100v1 Announce Type: cross Abstract: Fashion Image Captioning (FIC) plays a vital role in enhancing user experience and product search in e-commerce platforms. Unlike natural scene image

applicationsarxiv-cs-ai

Rank-Consistent Set Reasoning for Co-Salient Object Detection

arXiv:2609.13706v1 Announce Type: new Abstract: Co-salient object detection (Co-SOD) requires a model to find foreground regions that are salient in individual images and supported by the image group.

Scalability and Performance Evaluation of Federated Learning Frameworks: A Comparative Analysis

arXiv:2609.15681v1 Announce Type: cross Abstract: This paper presents a systematic examination and experimental comparison of the prominent Federated Learning (FL) frameworks FedML, Flower, Substra, a

applicationsarxiv-cs-ai

Hardware

Scaling Federated Learning Across Docker, Kubernetes, and Slurm with NVIDIA FLARE

NVIDIA FLARE separates persistent federation services from dynamically launched job workers, allowing each participating site to deploy federated learning jobs on Docker, Kubernetes, or Slurm without

hardwarenvidia-developer

Similar Accuracy, Unequal Evidence: Search APIs as Decision Surfaces for Tool-Using Agents

arXiv:2607.10198v2 Announce Type: replace Abstract: Search APIs expose ranked snippets, URLs, and metadata on which agents decide whether to answer, search again, or fetch pages. We evaluate these int

Sparsity-Adaptive Sharpness-Aware Minimization

arXiv:2609.14274v1 Announce Type: new Abstract: Deploying deep neural networks in real-world settings requires models that are both compact and robust to common corruptions. However, at deployment-rel

applicationsarxiv-cs-cv

STAGE: Diagnosing Semantic Transfer at Grounded Execution in Embodied Agents

arXiv:2609.13458v1 Announce Type: cross Abstract: Embodied language grounding requires more than identifying the referent of an instruction: recovered semantics must also control the action an agent e

TestHallVQA: Exploring LVLMs' Document-Level Reasoning under Redundant Contexts from Scientific Exams

arXiv:2609.13158v1 Announce Type: new Abstract: Large Vision--Language Models (LVLMs) are increasingly expected to perform visual question answering (VQA) over planar media. However, existing planar V

Toward Self-Adaptive Physical AI: Can LLM Agents Manage Long-Horizon Physical Tasks?

arXiv:2609.13436v1 Announce Type: new Abstract: Large Language Model (LLM) agents offer a promising path toward autonomously managing long-term physical tasks without human intervention. However, phys

agentsarxiv-cs-ai

TypiCore: A Hybrid Active Query Strategy for Class-Incremental Learning on Time Series

arXiv:2607.17632v2 Announce Type: replace-cross Abstract: Time series data play a pivotal role across numerous domains, including healthcare and manufacturing. In real-world environments, models must

Verifiable by Construction: Claim-Level Evaluation of Verbatim Citation in Clinical Question Answering

arXiv:2609.15964v1 Announce Type: new Abstract: Large language models (LLMs) have been widely adopted for clinical question answering (QA). Current systems can attach citations to their answers, but t

Zero-shot video highlight detection based on text descriptions and synthetic images

arXiv:2609.14790v1 Announce Type: new Abstract: Detecting video highlights, the most informative or engaging moments in a video, is important for applications such as video summarization and content r

CoralscapesV2: Panoptic and Fine-Grained Visual Scene Understanding in Coral Reefs

arXiv:2609.12826v1 Announce Type: new Abstract: In order to design conservation and restoration strategies to counter the global decline of coral reefs, ecological monitoring of reefs needs to be scal

DynSHAP: Towards Explainable Dynamic Survival Analysis

arXiv:2609.13042v1 Announce Type: new Abstract: Deep learning models for dynamic survival analysis (DSA) achieve strong predictive performance by incorporating longitudinal patient data, but their bla

applicationsarxiv-cs-lg

ESTS at WMT26: Routing-Informed Expert Pruning for Model Compression

arXiv:2609.12310v1 Announce Type: new Abstract: We describe six submissions under the team name ESTS to the unconstrained WMT26 Model Compression Shared Task for English--Simplified Chinese and Englis

Explainable Prediction from Mobile Sensing Data through LLM-guided Concept Integration

arXiv:2609.11995v1 Announce Type: new Abstract: Mobile sensing enables longitudinal monitoring of behavioral and physiological patterns in everyday settings. However, accurate prediction remains chall

researcharxiv-cs-lg

Inferring Dislocation Microstructures from X-ray Diffraction via Cross-Modal Contrastive Learning

arXiv:2609.12713v1 Announce Type: cross Abstract: Understanding and inferring dislocation microstructures from diffraction patterns remains an open challenge in materials characterization, as diffract

safetyarxiv-cs-lg

Local Ai

LG-PF: Lightweight Confidence-Guided Polarization Image Fusion

arXiv:2609.12787v1 Announce Type: new Abstract: Polarization image fusion combines the stable luminance and structural information of the total- intensity image S0 with the material-sensitive details

local-aiarxiv-cs-cv

OphBiWSSD: Scaling Temporal Action Localization in Ophthalmic Surgeries with Bidirectional Weight-tied State Space Duality

arXiv:2609.12409v1 Announce Type: new Abstract: High-frequency surgical maneuvers in ophthalmology necessitate high-fidelity temporal modeling, yet characterizing long-range procedural dependencies re

Physics-Aware Video Generation via Agentic Planning and Graph-Guided Optimization

arXiv:2609.13006v1 Announce Type: new Abstract: Video diffusion models (VDMs) have demonstrated remarkable capabilities in synthesizing high-fidelity, photorealistic video content. However, they funda

agentsarxiv-cs-cv

Reinforcement Learning over Patient Trajectories for Clinical Reasoning in EHR Foundation Models

arXiv:2609.12277v1 Announce Type: new Abstract: Electronic health record (EHR) foundation models trained on longitudinal patient trajectories have demonstrated strong performance across diverse clinic

safetyarxiv-cs-lg