Search: “multimodal”

Parameter-efficient Quantum Multi-task Learning

model-releasesarxiv-cs-lg

arXiv:2604.13560v1 Announce Type: new Abstract: Multi-task learning (MTL) improves generalization and data efficiency by jointly learning related tasks through shared representations. In the widely us

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Quantum Machine Learning for Colorectal Cancer Data: Anastomotic Leak Classification and Risk Factors

DGX agent

arXiv:2604.13951v1 Announce Type: new Abstract: This study evaluates colorectal risk factors and compares classical models against Quantum Neural Networks (QNNs) for anastomotic leak prediction. Analy

researcharxiv-cs-lg

16 Apr 2026

RadarSplat-RIO: Indoor Radar-Inertial Odometry with Gaussian Splatting-Based Radar Bundle Adjustment

arXiv:2604.13492v1 Announce Type: cross Abstract: Radar is more resilient to adverse weather and lighting conditions than visual and Lidar simultaneous localization and mapping (SLAM). However, most r

Reconstruction of a 3D wireframe from a single line drawing via generative depth estimation

arXiv:2604.13549v1 Announce Type: new Abstract: The conversion of 2D freehand sketches into 3D models remains a pivotal challenge in computer vision, bridging the gap between human creativity and digi

Robust Ultra Low-Bit Post-Training Quantization via Stable Diagonal Curvature Estimate

arXiv:2604.13806v1 Announce Type: new Abstract: Large Language Models (LLMs) are widely used across many domains, but their scale makes deployment challenging. Post-Training Quantization (PTQ) reduces

researcharxiv-cs-lg

Safe and Nonconservative Contingency Planning for Autonomous Vehicles via Online Learning-Based Reachable Set Barriers

arXiv:2509.07464v2 Announce Type: replace Abstract: Autonomous vehicles must navigate dynamically uncertain environments while balancing safety and efficiency. This challenge is exacerbated by unpredi

safetyarxiv-cs-ro

SceneGlue: Scene-Aware Transformer for Feature Matching without Scene-Level Annotation

arXiv:2604.13941v1 Announce Type: new Abstract: Local feature matching plays a critical role in understanding the correspondence between cross-view images. However, traditional methods are constrained

Hardware

SemiFA: An Agentic Multi-Modal Framework for Autonomous Semiconductor Failure Analysis Report Generation

arXiv:2604.13236v1 Announce Type: new Abstract: Semiconductor failure analysis (FA) requires engineers to examine inspection images, correlate equipment telemetry, consult historical defect records, a

hardwarearxiv-cs-cv

SiLVR: A Simple Language-based Video Reasoning Framework

arXiv:2505.24869v3 Announce Type: replace Abstract: Recent advances in test-time optimization have led to remarkable reasoning capabilities in Large Language Models (LLMs), enabling them to solve high

SparseBalance: Load-Balanced Long Context Training with Dynamic Sparse Attention

model-releasesarxiv-cs-lg

arXiv:2604.13847v1 Announce Type: new Abstract: While sparse attention mitigates the computational bottleneck of long-context LLM training, its distributed training process exhibits extreme heterogene

The Gaussian Latent Machine: Efficient Prior and Posterior Sampling for Inverse Problems

arXiv:2505.12836v2 Announce Type: replace-cross Abstract: We consider the problem of sampling from a product-of-experts-type model that encompasses many standard prior and posterior distributions comm

Tutorials

The noise we make is hurting animals. Can we learn to shut up?

When the covid-19 pandemic started, Jennifer Phillips thought about the songs of the sparrows. They were easier to hear, because the world had suddenly become quieter. Car traffic plummeted as people

tutorialsmit-tech-review

Agents

Towards Multi-Object-Tracking with Radar on a Fast Moving Vehicle: On the Potential of Processing Radar in the Frequency Domain

arXiv:2604.14013v1 Announce Type: cross Abstract: We promote in this paper the processing of radar data in the frequency domain to achieve higher robustness against noise and structural errors, especi

agentsarxiv-cs-cv

Towards Unconstrained Human-Object Interaction

arXiv:2604.14069v1 Announce Type: new Abstract: Human-Object Interaction (HOI) detection is a longstanding computer vision problem concerned with predicting the interaction between humans and objects.

ValueGround: Evaluating Culture-Conditioned Visual Value Grounding in MLLMs

model-releasesarxiv-cs-cl

arXiv:2604.06484v2 Announce Type: replace Abstract: Cultural values are expressed not only through language but also through visual scenes and everyday social practices. Yet existing evaluations of cu

AbdomenGen: Sequential Volume-Conditioned Diffusion Framework for Abdominal Anatomy Generation

arXiv:2604.12969v1 Announce Type: new Abstract: Computational phantoms are widely used in medical imaging research, yet current systems to generate controlled, clinically meaningful anatomical variati

Adaptive Domain Models: Bayesian Evolution, Warm Rotation, and Principled Training for Geometric and Neuromorphic AI

arXiv:2603.18104v3 Announce Type: replace Abstract: Prevailing AI training infrastructure assumes reverse-mode automatic differentiation over IEEE-754 arithmetic. The memory overhead of training relat

ARGen: Affect-Reinforced Generative Augmentation towards Vision-based Dynamic Emotion Perception

arXiv:2604.12255v1 Announce Type: cross Abstract: Dynamic facial expression recognition in the wild remains challenging due to data scarcity and long-tail distributions, which hinder models from effec

safetyarxiv-cs-ai

ASTRA: Let Arbitrary Subjects Transform in Video Editing

model-releasesarxiv-cs-cv

arXiv:2510.01186v2 Announce Type: replace Abstract: While existing video editing methods excel with single subjects, they struggle in dense, multi-subject scenes, frequently suffering from attention d

BINDER: Instantly Adaptive Mobile Manipulation with Open-Vocabulary Commands

arXiv:2511.22364v2 Announce Type: replace-cross Abstract: Open-vocabulary mobile manipulation (OVMM) requires robots to follow language instructions, navigate, and manipulate while updating their worl

Causal Diffusion Models for Counterfactual Outcome Distributions in Longitudinal Data

arXiv:2604.12992v1 Announce Type: cross Abstract: Predicting counterfactual outcomes in longitudinal data, where sequential treatment decisions heavily depend on evolving patient states, is critical y

safetyarxiv-cs-lg

Characterizing Resource Sharing Practices on Underground Internet Forum Synthetic Non-Consensual Intimate Image Content Creation Communities

arXiv:2604.12190v1 Announce Type: cross Abstract: Many malicious actors responsible for disseminating synthetic non-consensual intimate imagery (SNCII) operate within internet forums to exchange resou

Classification of Epileptic iEEG using Topological Machine Learning

arXiv:2604.11971v1 Announce Type: new Abstract: Epileptic seizure detection from EEG signals remains challenging due to the high dimensionality and nonlinear, potentially stochastic, dynamics of neura

researcharxiv-cs-lg

CODESTRUCT: Code Agents over Structured Action Spaces

model-releasesarxiv-cs-ai

arXiv:2604.05407v2 Announce Type: replace Abstract: LLM-based code agents treat repositories as unstructured text, applying edits through brittle string matching that frequently fails due to formattin

Combating Pattern and Content Bias: Adversarial Feature Learning for Generalized AI-Generated Image Detection

arXiv:2604.12353v1 Announce Type: new Abstract: In recent years, the rapid development of generative artificial intelligence technology has significantly lowered the barrier to creating high-quality f

safetyarxiv-cs-cv

CropVLM: Learning to Zoom for Fine-Grained Vision-Language Perception

arXiv:2511.19820v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) often struggle with tasks that require fine-grained image understanding, such as scene-text recognition or docum

Cross-Modal Knowledge Distillation for PET-Free Amyloid-Beta Detection from MRI

arXiv:2604.12574v1 Announce Type: new Abstract: Detecting amyloid-eta (Aeta) positivity is crucial for early diagnosis of Alzheimer's disease but typically requires PET imaging, which is costly, invas

safetyarxiv-cs-cv

Curvelet-Based Frequency-Aware Feature Enhancement for Deepfake Detection

arXiv:2604.12028v1 Announce Type: cross Abstract: The proliferation of sophisticated generative models has significantly advanced the realism of synthetic facial content, known as deepfakes, raising s

Agents

Cutting edge of digital art with Hermes Agent

Nous Research's Hermes Agent demonstrates advanced capabilities in generating digital art, showcasing how AI agents can autonomously create or assist in producing visual artwork at a sophisticated lev

agentsnous-research--x

Fall Risk and Gait Analysis in Community-Dwelling Older Adults using World-Spaced 3D Human Mesh Recovery

arXiv:2604.11961v1 Announce Type: new Abstract: Gait assessment is a key clinical indicator of fall risk and overall health in older adults. However, standard clinical practice is largely limited to s

Local Ai

FMASH: Advancing Traditional Chinese Medicine Formula Recommendation with Efficient Fusion of Multiscale Associations of Symptoms and Herbs

arXiv:2503.05167v3 Announce Type: replace Abstract: Traditional Chinese medicine (TCM) exhibits remarkable therapeutic efficacy in healthcare through patient-specific formulas. However, current AI-bas

local-aiarxiv-cs-lg

Fragile Reconstruction: Adversarial Vulnerability of Reconstruction-Based Detectors for Diffusion-Generated Images

arXiv:2604.12781v1 Announce Type: new Abstract: Recently, detecting AI-generated images produced by diffusion-based models has attracted increasing attention due to their potential threat to safety. A

safetyarxiv-cs-cv

GCA Framework: A Gulf-Grounded Dataset and Agentic Pipeline for Climate Decision Support

model-releasesarxiv-cs-ai

arXiv:2604.12306v1 Announce Type: cross Abstract: Climate decision-making in the Gulf increasingly demands systems that can translate heterogeneous scientific and policy evidence into actionable guida

HiCoLoRA: Addressing Context-Prompt Misalignment via Hierarchical Collaborative LoRA for Zero-Shot DST

arXiv:2509.19742v4 Announce Type: replace-cross Abstract: Zero-shot Dialog State Tracking (zs-DST) is essential for enabling Task-Oriented Dialog Systems (TODs) to generalize to new domains without co

safetyarxiv-cs-ai

Information-Theoretic Optimization for Task-Adapted Compressed Sensing Magnetic Resonance Imaging

arXiv:2604.12709v1 Announce Type: cross Abstract: Task-adapted compressed sensing magnetic resonance imaging (CS-MRI) is emerging to address the specific demands of downstream clinical tasks with sign

Is Sliding Window All You Need? An Open Framework for Long-Sequence Recommendation

arXiv:2604.12372v1 Announce Type: new Abstract: Long interaction histories are central to modern recommender systems, yet training with long sequences is often dismissed as impractical under realistic

researcharxiv-cs-lg

LaV-CoT: Language-Aware Visual CoT with Multi-Aspect Reward Optimization for Real-World Multilingual VQA

model-releasesarxiv-cs-cv

arXiv:2509.10026v4 Announce Type: replace Abstract: As large vision language models (VLMs) advance, their capabilities in multilingual visual question answering (mVQA) have significantly improved. Cha

Learning Versatile Humanoid Manipulation with Touch Dreaming

arXiv:2604.13015v1 Announce Type: new Abstract: Humanoid robots promise general-purpose assistance, yet real-world humanoid loco-manipulation remains challenging because it requires whole-body stabili

safetyarxiv-cs-ro

Tutorials

Listening Deepfake Detection: A New Perspective Beyond Speaking-Centric Forgery Analysis

arXiv:2604.12650v1 Announce Type: new Abstract: Existing deepfake detection research has primarily focused on scenarios where the manipulated subject is actively speaking, i.e., generating fabricated

tutorialsarxiv-cs-cv

LLM-Based Automated Diagnosis Of Integration Test Failures At Google

arXiv:2604.12108v1 Announce Type: cross Abstract: Integration testing is critical for the quality and reliability of complex software systems. However, diagnosing their failures presents significant c

Tutorials

LLM-Guided Task- and Affordance-Level Exploration in Reinforcement Learning

arXiv:2509.16615v2 Announce Type: replace Abstract: Reinforcement learning (RL) is a promising approach for robotic manipulation, but it can suffer from low sample efficiency and requires extensive ex

tutorialsarxiv-cs-ro

LLM-HYPER: Generative CTR Modeling for Cold-Start Ad Personalization via LLM-Based Hypernetworks

arXiv:2604.12096v1 Announce Type: new Abstract: On online advertising platforms, newly introduced promotional ads face the cold-start problem, as they lack sufficient user feedback for model training.

MedConcept: Unsupervised Concept Discovery for Interpretability in Medical VLMs

model-releasesarxiv-cs-cv

arXiv:2604.11868v1 Announce Type: new Abstract: While medical Vision-Language models (VLMs) achieve strong performance on tasks such as tumor or organ segmentation and diagnosis prediction, their opaq

Neural Dynamic GI: Random-Access Neural Compression for Temporal Lightmaps in Dynamic Lighting Environments

arXiv:2604.12625v1 Announce Type: cross Abstract: High-quality global illumination (GI) in real-time rendering is commonly achieved using precomputed lighting techniques, with lightmap as the standard

NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: Professional Image Quality Assessment (Track 1)

model-releasesarxiv-cs-ai

arXiv:2604.12512v1 Announce Type: cross Abstract: In this paper, we present an overview of the NTIRE 2026 challenge on the 3rd Restore Any Image Model in the Wild, specifically focusing on Track 1: Pr

Observing the unobserved confounding through its effects: toward randomized trial-like estimates from real-world survival data

arXiv:2604.12137v1 Announce Type: cross Abstract: Background: Randomized controlled trials (RCTs) are costly, time-consuming, and often infeasible, while treatment-effect estimation from observational

OmniFood8K: Single-Image Nutrition Estimation via Hierarchical Frequency-Aligned Fusion

arXiv:2604.12356v1 Announce Type: new Abstract: Accurate estimation of food nutrition plays a vital role in promoting healthy dietary habits and personalized diet management. Most existing food datase

OSC: Hardware Efficient W4A4 Quantization via Outlier Separation in Channel Dimension

arXiv:2604.12782v1 Announce Type: cross Abstract: While 4-bit quantization is essential for high-throughput deployment of Large Language Models, activation outliers often lead to significant accuracy