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arXiv:2605.01916v1 Announce Type: new Abstract: Infrared-visible image fusion aims to create an information-rich fused image by integrating the complementary thermal saliency from infrared sensing and

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Exploring Data-Free LoRA Transferability for Video Diffusion Models

DGX agent

arXiv:2605.01929v1 Announce Type: new Abstract: Video diffusion models leveraging step distillation or causal distillation have achieved remarkable performance. However, adapting existing LoRAs to the

safetyarxiv-cs-cv

5 May 2026

Fine-Grained Class-Conditional Distribution Balancing for Debiased Learning

arXiv:2505.06831v2 Announce Type: replace Abstract: Achieving group-robust generalization in the presence of spurious correlations remains a significant challenge, particularly when bias annotations a

G-reasoner: Foundation Models for Unified Reasoning over Graph-structured Knowledge

model-releasesarxiv-cs-ai

arXiv:2509.24276v4 Announce Type: replace Abstract: Large language models (LLMs) excel at complex reasoning but remain limited by static and incomplete parametric knowledge. Retrieval-augmented genera

General Frameworks for Conditional Two-Sample Testing

arXiv:2410.16636v2 Announce Type: replace-cross Abstract: We study the problem of conditional two-sample testing, which aims to determine whether two populations have the same distribution after accou

safetyarxiv-cs-lg

HiFi-Mamba: Dual-Stream W-Laplacian Enhanced Mamba for High-Fidelity MRI Reconstruction

arXiv:2508.09179v3 Announce Type: replace-cross Abstract: Reconstructing high-fidelity MR images from undersampled k-space data remains a challenging problem in MRI. While Mamba variants for vision ta

How Can One Choose the Best CAM-Based Explainability Method for a CNN Model?

arXiv:2605.02007v1 Announce Type: cross Abstract: In recent years, several advances have been observed in Deep Learning with surprising results. Models in this area have been increasingly used in nume

Is It Novel and Why? Fine-Grained Patent Novelty Prediction Based on Passage Retrieval

arXiv:2605.02392v1 Announce Type: new Abstract: Novelty assessment is a critical yet complex task in the examination process for patent acceptance, requiring examiners to determine whether an inventio

researcharxiv-cs-cl

Kinematic Kitbashing

arXiv:2510.13048v2 Announce Type: replace Abstract: We introduce Kinematic Kitbashing, an optimization framework that synthesizes articulated 3D objects by assembling reusable parts conditioned on an

researcharxiv-cs-ro

Tutorials

Learn-to-learn on Arbitrary Textual Conditioning: A Hypernetwork-Driven Meta-Gated LLM

arXiv:2605.01973v1 Announce Type: new Abstract: Conventional LLMs may suffer from corpus heterogeneity and subtle condition changes. While finetuning can create the catastrophe forgetting issue, appli

tutorialsarxiv-cs-cl

Leveraging Imperfect Medical Data: A Manifold-Consistent Spatio-Temporal Network for Sensor-based Human Activity Recognition

arXiv:2605.00913v1 Announce Type: new Abstract: Sensor-based Human Activity Recognition (HAR) has attracted increasing attention in medical and healthcare monitoring, particularly with the growth of I

Low-Latency Embedded Driver Monitoring System with a Multi-Task Neural Network

arXiv:2605.02563v1 Announce Type: new Abstract: Road traffic accidents remain a significant global concern, with the majority attributed to human factors such as driver distraction and fatigue. This s

Mamoda2.5: Enhancing Unified Multimodal Model with DiT-MoE

arXiv:2605.02641v1 Announce Type: new Abstract: We present Mamoda2.5, a unified AR-Diffusion framework that seamlessly integrates multimodal understanding and generation within a single architecture.

MooD: An Efficient VA-Driven Affective Image Editing Framework via Fine-Grained Semantic Control

arXiv:2605.02521v1 Announce Type: new Abstract: Affective image editing (AIE) aims to edit visual content to evoke target emotions. However, existing methods often overlook inference efficiency and pr

MorphIt: Flexible Spherical Approximation of Robot Morphology for Representation-driven Adaptation

model-releasesarxiv-cs-ro

arXiv:2507.14061v2 Announce Type: replace Abstract: What if a robot could rethink its own morphological representation to better meet the demands of diverse tasks? Most robotic systems today treat the

Multi-fidelity surrogates for mechanics of composites: from co-kriging to multi-fidelity neural networks

arXiv:2605.02871v1 Announce Type: cross Abstract: Composite materials exhibit strongly hierarchical and anisotropic properties governed by coupled mechanisms spanning constituents, plies, laminates, s

Observability Conditions and Filter Design for Visual Pose Estimation via Dual Quaternions

arXiv:2605.02054v1 Announce Type: cross Abstract: This paper presents a dual quaternion framework for 6-DOF visual target tracking that addresses key limitations of perspective-n-point (PnP) solvers:

OceanPile: A Large-Scale Multimodal Ocean Corpus for Foundation Models

model-releasesarxiv-cs-cl

arXiv:2605.00877v1 Announce Type: cross Abstract: The vast and underexplored ocean plays a critical role in regulating global climate and supporting marine biodiversity, yet artificial intelligence ha

On Stable Long-Form Generation: Benchmarking and Mitigating Length Volatility

model-releasesarxiv-cs-cl

arXiv:2605.01357v1 Announce Type: new Abstract: Large Language Models (LLMs) excel at long-context understanding but exhibit significant limitations in long-form generation. Existing studies primarily

Agents

PACE: Post-Causal Entropy Modeling for Learned LiDAR Point Cloud Compression

arXiv:2605.01320v1 Announce Type: new Abstract: LiDAR point cloud compression is vital for autonomous systems to handle massive data from high-resolution sensors. While learned entropy modeling built

agentsarxiv-cs-cv

Parameter Space Analysis through Guided Visual Interpolations

arXiv:2509.19202v2 Announce Type: replace-cross Abstract: We propose Parameter Space Analysis through Guided Visual Interpolations (ParamInter), a novel tool for high-dimensional input parameter space

ParaRNN: An Interpretable and Parallelizable Recurrent Neural Network for Time-Dependent Data

arXiv:2605.02692v1 Announce Type: cross Abstract: The proliferation of large-scale and structurally complex data has spurred the integration of machine learning methods into statistical modeling. Recu

PepSpecBench: A Unified Evaluation Benchmark for Peptide Tandem Mass Spectrometry Prediction

arXiv:2605.01945v1 Announce Type: new Abstract: Tandem mass spectrometry provides a high-throughput framework for identifying and quantifying proteins in complex biological samples. In computational p

Physics-Informed Neural Learning for State Reconstruction and Parameter Identification in Coupled Greenhouse Climate Dynamics

arXiv:2605.02524v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have recently emerged as a promising framework for integrating data-driven learning with physical knowledge. In

Pi-Change: A Prior-Informed Multiple Change Point Detection Algorithm

arXiv:2605.01003v1 Announce Type: cross Abstract: Statistical change point (CP) detection methods typically rely on likelihood-based inference and ignore contextual information about plausible CP loca

Tutorials

PiCSRL: Physics-Informed Contextual Spectral Reinforcement Learning

arXiv:2603.26816v2 Announce Type: replace Abstract: High-dimensional low-sample-size (HDLSS) datasets constrain reliable environmental model development, where labeled data remain sparse. Reinforcemen

tutorialsarxiv-cs-lg

Revisiting Semantic Role Labeling: Efficient Structured Inference with Dependency-Informed Analysis

arXiv:2605.02505v1 Announce Type: new Abstract: Semantic Role Labeling (SRL) provides an explicit representation of predicate-argument structure, capturing linguistically grounded relations such as wh

researcharxiv-cs-cl

SAMamba3D: adapting Segment Anything for generalizable 3D segmentation of multiphase pore-scale images

arXiv:2605.00916v1 Announce Type: new Abstract: Reliable segmentation of multiphase pore-scale X-ray images of rocks is necessary to quantify fluid saturation, connectivity, and interfacial geometry.

SHARP: Spectrum-aware Highly-dynamic Adaptation for Resolution Promotion in Remote Sensing Synthesis

arXiv:2603.21783v2 Announce Type: replace Abstract: Text-to-image generation powered by Diffusion Transformers (DiTs) has made remarkable strides, yet remote sensing (RS) synthesis lags behind due to

Agents

Sim-to-Real Transfer and Robustness Evaluation of Reinforcement Learning Control with Integrated Perception on an ASV for Floating Waste Capture

arXiv:2605.02529v1 Announce Type: new Abstract: Autonomous surface vessels for floating-waste removal operate under varying hydrodynamics, external disturbances, and challenging water-surface percepti

agentsarxiv-cs-ro

SixthSense: Task-Agnostic Proprioception-Only Whole-Body Wrench Estimation for Humanoids

arXiv:2605.01427v1 Announce Type: new Abstract: Humanoid robots are entering our physical world at scale, yet as oversized toys--good at singing and dancing, but short on force-interaction capabilitie

researcharxiv-cs-ro

SparseContrast: Dynamic Sparse Attention for Efficient and Accurate Contrastive Learning in Medical Imaging

arXiv:2605.00887v1 Announce Type: new Abstract: We propose SparseContrast, a new framework that merges dynamic sparse attention with contrastive learning for medical imaging, with a focus on chest X-r

Stability and Generalization for Decentralized Markov SGD

arXiv:2605.01701v1 Announce Type: new Abstract: Stochastic gradient methods are central to large-scale learning, yet their generalization theory typically relies on independent sampling assumptions. I

Stable Blanket with Hidden Variables and Cycles

arXiv:2605.01856v1 Announce Type: cross Abstract: Stabilized regression aims to identify a set of predictors whose conditional relationship with a response variable remains invariant across different

Local Ai

Super-resolution of airborne laser scanning point clouds for forest inventory

arXiv:2605.02201v1 Announce Type: new Abstract: Airborne Laser Scanning (ALS) can collect point clouds across large areas, enabling large-scale forest inventory. However, ALS point clouds are sparse a

local-aiarxiv-cs-cv

SwiftPie: Lightning-fast Subject-driven Image Personalization via One step Diffusion

arXiv:2605.01510v1 Announce Type: new Abstract: Diffusion models have achieved remarkable success in high-quality image synthesis, sparking interest in image-guided generation tasks such as subject-dr

Synthetic Users, Real Differences: an Evaluation Framework for User Simulation in Multi-Turn Conversations

arXiv:2605.02624v1 Announce Type: new Abstract: There is growing interest in exploring user simulation as an alternative to gathering and scoring real user-chatbot interactions for AI chatbot evaluati

researcharxiv-cs-cl

Task-Related Token Compression in Multimodal Large Language Models from an Explainability Perspective

arXiv:2506.01097v2 Announce Type: replace Abstract: Existing Multimodal Large Language Models (MLLMs) process a large number of visual tokens, leading to significant computational costs and inefficien

The Banach-Butterfly Invariant: Influence-Adaptive Walsh Geometry for Ternary Polynomial Threshold Functions

arXiv:2605.01637v1 Announce Type: new Abstract: We introduce the Banach-Butterfly Invariant (BBT), an influence-adaptive Banach geometry on the Walsh-Hadamard butterfly factorization. For a Boolean fu

The Good, the Bad, and the Sampled: a No-Regret Approach to Safe Online Classification

arXiv:2510.01020v2 Announce Type: replace Abstract: We study sequential testing for a binary disease outcome when risk follows an unknown logistic model. At each round, the decision maker may either p

To Do or Not to Do: Ensuring the Safety of Visuomotor Policies Learned from Demonstrations

arXiv:2605.01201v1 Announce Type: new Abstract: Task success has historically been the primary measure of policy performance in imitation learning (IL) research. This characteristics strictly limits t

safetyarxiv-cs-ro

TRIM: A Self-Supervised Video Summarization Framework Maximizing Temporal Relative Information and Representativeness

arXiv:2506.20588v2 Announce Type: replace Abstract: The increasing ubiquity of video content and the corresponding demand for efficient access to meaningful information have elevated video summarizati

TRIP-Evaluate: An Open Multimodal Benchmark for Evaluating Large Models in Transportation

arXiv:2605.00907v1 Announce Type: new Abstract: Large language models (LLMs) and multimodal large models (MLLMs) are increasingly used for transportation tasks such as regulation question answering, t

Unbox Responsible GeoAI: Navigating Climate Extreme and Disaster Mapping

arXiv:2605.00315v1 Announce Type: cross Abstract: As climate extreme and disaster events become more frequent and intense, Geospatial Artificial Intelligence (GeoAI) has emerged as a transformative ap

researcharxiv-cs-ai

Visual Chart Representations for Cryptocurrency Regime Prediction: A Systematic Deep Learning Study

arXiv:2605.00875v1 Announce Type: new Abstract: Technical traders have long relied on visual analysis of candlestick charts to identify market patterns and predict price movements. While deep learning

WILD SAM: A Simulated-and-Real Data Augmentation for Autonomous Driving Perception under Challenging Weather

arXiv:2605.01081v1 Announce Type: new Abstract: The performance of state-of-the-art object detectors degrades significantly under adverse weather, causing a safety-critical domain shift problem for au

Zero-Shot Adaptation of Behavioral Foundation Models to Unseen Dynamics

arXiv:2505.13150v2 Announce Type: replace Abstract: Behavioral Foundation Models (BFMs) proved successful in producing policies for arbitrary tasks in a zero-shot manner, requiring no test-time traini

safetyarxiv-cs-lg

Zero-Shot Interpretable Image Steganalysis for Invertible Image Hiding

arXiv:2605.01331v1 Announce Type: new Abstract: Image steganalysis, which aims at detecting secret information concealed within images, has become a critical countermeasure for assessing the security