Search: “framework”

Adaptive Residual-Update Steering for Low-Overhead Hallucination Mitigation in Large Vision Language Models

arXiv:2511.10292v2 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) typically process visual inputs as a prefix to the language decoder. As the model autoregressively genera

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An Empirical Investigation of Reconstruction-Based Models for Seizure Prediction from ECG Signals

DGX agent

arXiv:2504.08381v2 Announce Type: replace-cross Abstract: Epileptic seizures are transient neurological events characterized by abnormal and excessive neuron activity in the brain, which are often ass

applicationsarxiv-cs-lg

20 May 2026

An Objective Performance Evaluation of the LSTM Networks in Time Series Classification

arXiv:2605.19311v1 Announce Type: new Abstract: The rapid adoption of deep learning has increasingly led to data-driven models replacing classical model-based algorithms, even in domains governed by w

AnchorFlow: Editable SVG Reconstruction via Sparse Anchor Point Fields

arXiv:2605.19551v1 Announce Type: cross Abstract: Image-to-SVG reconstruction aims to produce vector graphics that are faithful to raster inputs and easy to edit. Existing methods face a structural tr

Are Tools Always Beneficial? Learning to Invoke Tools Adaptively for Dual-Mode Multimodal LLM Reasoning

model-releasesarxiv-cs-cl

arXiv:2605.19852v1 Announce Type: new Abstract: Tool-augmented reasoning has emerged as a promising direction for enhancing the reasoning capabilities of multimodal large language models (MLLMs). Howe

Are Watermarked Images Editable? SafeMark for Watermark-Preserving Text-Guided Image Editing

arXiv:2605.19511v1 Announce Type: new Abstract: This paper investigates a fundamental yet underexplored question: can watermarked images remain editable without compromising watermark integrity? We pr

Atomistic Modeling of Chemical Disorder in Materials: Bridging Classical Methods and AI-Assisted Approaches

arXiv:2605.19124v1 Announce Type: cross Abstract: Chemical disorder, originating from the mixed occupation of crystallographic sites by multiple elements, is widespread in alloys, ceramics, and compos

safetyarxiv-cs-lg

Automated Big Data Quality Assessment using Knowledge Graph Embeddings

arXiv:2605.18833v1 Announce Type: cross Abstract: Automated data quality assessment is crucial for managing big data, but existing solutions face challenges in achieving accurate context-aware assessm

applicationsarxiv-cs-ai

Automatically Improving Simulation Physics for Articulated Objects

arXiv:2605.19136v1 Announce Type: new Abstract: Simulation is a central tool for scalable robot learning, but its effectiveness depends on the quality of object assets. While modern 3D datasets provid

safetyarxiv-cs-ro

Awakening the Hydra: Stabilizing Multi-Concept Backdoor Injection in Text-to-Image Diffusion Models

arXiv:2605.19698v1 Announce Type: cross Abstract: Text-to-image diffusion models are increasingly developed through open-source reuse and repeated downstream fine-tuning, where reused checkpoints are

Bayesian Joint Model of Multi-Sensor and Failure Event Data for Multi-Mode Failure Prediction

arXiv:2506.17036v2 Announce Type: replace-cross Abstract: Modern industrial systems are often subject to multiple failure modes, and their conditions are monitored by multiple sensors, generating mult

Bayesian Latent Space Models for Graphs Are Misspecified: Toward Robust Inference via Generalized Posteriors

arXiv:2605.18927v1 Announce Type: cross Abstract: Bayesian latent space models offer a principled approach to network representation, but rely on correct specification of both geometry and link functi

applicationsarxiv-cs-lg

BERTO: Intent-Driven Network Time Series Forecasting via Natural Language Operator Preferences

arXiv:2512.05721v2 Announce Type: replace Abstract: Traditional cellular traffic forecasting models are optimized for minimizing symmetric errors, leaving them indifferent to shifting operational prio

safetyarxiv-cs-lg

Beyond Imitation: Learning Safe End-to-End Autonomous Driving from Hard Negatives

model-releasesarxiv-cs-cv

arXiv:2605.19771v1 Announce Type: cross Abstract: Existing imitation learning methods for end-to-end autonomous driving predominantly learn from successful demonstrations by minimizing geometric devia

Beyond Leakage and Complexity: Towards Realistic and Efficient Information Cascade Prediction

arXiv:2510.25348v2 Announce Type: replace Abstract: Information cascade popularity prediction is a key problem in analyzing content diffusion in social networks. However, current related works suffer

applicationsarxiv-cs-lg

Beyond Majority Voting: LLM Aggregation by Leveraging Higher-Order Information

arXiv:2510.01499v2 Announce Type: replace-cross Abstract: With the rapid progress of multi-agent large language model (LLM) reasoning, how to effectively aggregate answers from multiple LLMs has emerg

agentsarxiv-cs-ai

Bezier Degradation Modeling for LiDAR-based Human Motion Capture

arXiv:2605.19620v1 Announce Type: new Abstract: LiDAR-based 3D human motion capture has broad applications in fields such as autonomous driving and robotics, where accurate motion reconstruction is cr

agentsarxiv-cs-cv

Bilateral Teleoperation with Compliant 6-DOF Pose-and-Force Sensing

arXiv:2605.19255v1 Announce Type: new Abstract: Existing bilateral teleoperation platforms still rely on costly rigid six-axis force/torque sensors, tightly coupled leader-follower hardware, and kiloh

researcharxiv-cs-ro

BLINKG: A Benchmark for LLM-Integrated Knowledge Graph Generation

model-releasesarxiv-cs-ai

arXiv:2605.19518v1 Announce Type: new Abstract: Generating Knowledge Graphs (KGs) remains one of the most time-consuming and labor-intensive tasks for knowledge engineers, as they need to identify sem

Breaking Modality Heterogeneity in Low-Bit Quantization for Large Vision-Language Models

arXiv:2605.19929v1 Announce Type: cross Abstract: Low-bit post-training quantization (PTQ) is a pivotal technique for deploying Vision-Language Models (VLMs) on resource-constrained devices. However,

Bridge: Retrieval-Augmented Spatiotemporal Modeling for Urban Delivery Demand

arXiv:2605.19172v1 Announce Type: cross Abstract: Forecasting urban delivery demand becomes substantially more challenging when newly added service regions lack historical records. Existing spatiotemp

applicationsarxiv-cs-ai

CAMERA: Adapting to Semantic Camouflage in Unsupervised Text-Attributed Graph Fraud Detection

arXiv:2605.20032v1 Announce Type: new Abstract: Text-attributed graph fraud detection (TAGFD) plays a critical role in preventing fraudulent activities on online social and e-commerce platforms. Howev

CaMo: Camera Motion Grounded Evaluation and Training for Vision-Language Models

arXiv:2605.20165v1 Announce Type: new Abstract: Vision-Language Models (VLMs) achieve strong performance on spatial question answering benchmarks, yet it remains unclear whether such gains reflect gen

Can Large Language Models Revolutionize Survey Research? Experiments with Disaster Preparedness Responses

arXiv:2605.19229v1 Announce Type: new Abstract: Survey research faces mounting structural challenges: declining response rates, sample bias, block-wise missingness among at-risk respondents, and AI-as

CANTANTE: Optimizing Agentic Systems via Contrastive Credit Attribution [R]

CANTANTE addresses the challenge of optimizing LLM-based multi-agent systems where system-level performance scores are available but individual agent parameters cannot be directly optimized. The frame

agentsr-machinelearning

Tutorials

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

ClinSeekAgent: Automating Multimodal Evidence Seeking for Agentic Clinical Reasoning

model-releasesarxiv-cs-cl

arXiv:2605.20176v1 Announce Type: new Abstract: Large language models (LLMs) and agentic systems have shown promise for clinical decision support, but existing works largely assume that evidence has a

CMAD: Cooperative Multi-Agent Diffusion via Stochastic Optimal Control

arXiv:2602.10933v2 Announce Type: replace Abstract: Continuous-time generative models have achieved remarkable success in image restoration and synthesis. However, controlling the composition of multi

agentsarxiv-cs-lg

CogScale: Scalable Benchmark for Sequence Processing

model-releasesarxiv-cs-ai

arXiv:2605.19758v1 Announce Type: new Abstract: The ability to maintain and manipulate information over time is a fundamental aspect of living beings and Artificial Intelligence. While modern models h

CoLD: Counterfactually-Guided Length Debiasing for Process Reward Models in Mathematical Reasoning

arXiv:2507.15698v2 Announce Type: replace-cross Abstract: Process Reward Models (PRMs) play a central role in evaluating and guiding multi-step reasoning in large language models (LLMs), especially fo

Complexity Analysis of Normalizing Constant Estimation: from Jarzynski Equality to Annealed Importance Sampling and beyond

arXiv:2502.04575v3 Announce Type: replace-cross Abstract: Given an unnormalized probability density piproptoe^{-V}, estimating its normalizing constant Z=int_{R^d}e^{-V(x)}dx or free energy F=-log Z i

Component-Aware Structure-Preserving Style Transfer for Satellite Sim2Real 6D Pose Estimation

arXiv:2605.19624v1 Announce Type: cross Abstract: Monocular 6D pose estimation for non-cooperative satellites depends heavily on annotated training data, yet real satellite images with reliable pose l

Composition of Memory Experts for Diffusion World Models

arXiv:2605.18813v1 Announce Type: cross Abstract: World models aim to predict plausible futures consistent with past observations, a capability central to planning and decision-making in reinforcement

applicationsarxiv-cs-ai

Concept-Guided Noisy Negative Suppression for Zero-Shot Classification and Grounding of Chest X-Ray Findings

arXiv:2605.19374v1 Announce Type: cross Abstract: Vision-language alignment using chest X-rays and radiology reports has emerged as an advanced paradigm for zero-shot classification and grounding of c

Context-Aware Detection and Victim-Centered Response Generation for Online Harassment in Private Messaging

arXiv:2512.14700v2 Announce Type: replace-cross Abstract: Online harassment is a widespread social and public health concern, yet most computational approaches for detecting and addressing harassment

researcharxiv-cs-cl

ContextFlow: Hierarchical Task-State Alignment for Long-Horizon Embodied Agents

arXiv:2605.19314v1 Announce Type: cross Abstract: Long-horizon embodied agents increasingly delegate navigation, search, approach, and manipulation to specialist executors. As these executors become s

Contextualized Visual Personalization in Vision-Language Models

arXiv:2602.03454v3 Announce Type: replace Abstract: Despite recent progress in vision-language models (VLMs), existing approaches often fail to generate personalized responses based on the user's spec

CPC-VAR:Continual Personalized and Compositional Generation in Visual Autoregressive Models

arXiv:2605.19750v1 Announce Type: new Abstract: Visual autoregressive (VAR) models have recently emerged as an efficient paradigm for text-to-image generation. Despite their strong generative capabili

CriterAlign: Criterion-Centric Rationale Alignment for Code Preference Judging

arXiv:2605.19665v1 Announce Type: cross Abstract: Pairwise human preference prediction is central to evaluating code-generation systems, where quality often depends on task-specific trade-offs beyond

Tutorials

Critique-Guided Distillation for Robust Reasoning via Refinement

arXiv:2505.11628v4 Announce Type: replace Abstract: Supervised fine-tuning with expert demonstrations often produces models that imitate outputs without internalizing the reasoning processes needed fo

tutorialsarxiv-cs-cl

Cross-Paradigm Knowledge Distillation: A Comprehensive Study of Bidirectional Transfer Between Random Forests and Deep Neural Networks for Big Data Applications

arXiv:2605.19299v1 Announce Type: new Abstract: The exponential growth of big data has intensified the need for efficient and interpretable machine learning models that can handle diverse data charact

Cross-Subject Intracranial EEG Reconstruction from Scalp Recordings Using Multi-Scale Cross-Attention Transformers

arXiv:2605.18897v1 Announce Type: cross Abstract: Intracranial EEG (iEEG) provides high-fidelity neural recordings essential for clinical and brain-computer interface applications, but acquiring these

D-Convexity: A Unified Differentiable Convex Shape Prior via Quasi-Concavity for Data-driven Image Segmentation

arXiv:2605.19210v1 Announce Type: new Abstract: Convexity is a fundamental geometric prior that underlies many natural and man-made structures, yet remains challenging to impose effectively in end-to-

D^3-Subsidy: Online and Sequential Driver Subsidy Decision-Making for Large-Scale Ride-Hailing Market

model-releasesarxiv-cs-lg

arXiv:2605.20036v1 Announce Type: new Abstract: Ride-hailing platforms like DiDi Chuxing operate in highly dynamic environments where balancing driver supply and passenger demand is critical. Although

Data-Free Client Contribution Estimation via Logit Maximization for Federated Learning

arXiv:2605.18892v1 Announce Type: cross Abstract: Federated learning (FL) enables collaborative learning of computer vision models, where privacy and regulatory constraints prevent centralizing data a

Hardware

Decentralized Direct Volume Rendering: A Browser-Native GPU Architecture for MRI Digital Twins in Resource-Constrained Settings

arXiv:2605.19737v1 Announce Type: cross Abstract: Digital Twin (DT) technology holds immense potential for surgical planning and personalized medicine. However, generating interactive, patient-specifi

hardwarearxiv-cs-cv

Tutorials

Diagnosing Multi-step Reasoning Failures in Black-box LLMs via Stepwise Confidence Attribution

arXiv:2605.19228v1 Announce Type: cross Abstract: Large Language Models have achieved strong performance on reasoning tasks with objective answers by generating step-by-step solutions, but diagnosing

tutorialsarxiv-cs-ai