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A Shared-Backbone Approach for Multi-Task MedMNIST Classification

arXiv:2609.06838v1 Announce Type: new Abstract: Multi-task biomedical classification requires models to generalize across disparate modalities and class distributions. We study 11 heterogeneous MedMNI

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A Survey on Adversarial Attacks and Defenses for Diffusion Models Across Multiple Modalities

DGX agent

arXiv:2609.05503v1 Announce Type: new Abstract: Diffusion models have become the dominant family of generative models in the visual domain. However, their widespread public availability enables misuse

researcharxiv-cs-cv

9 Sept 2026

A Systematic Analysis of Automatic Differentiation versus Discretization-based Constraints for Physics-Informed PDE Solvers

arXiv:2609.07437v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) represent a growing frontier in using artificial intelligence to solve partial differential equations (PDEs).

A Theoretical Analysis of Generalization Dynamics in Neural Networks under Gradient Descent with Weight Decay

arXiv:2609.07755v1 Announce Type: new Abstract: Understanding generalization remains a central challenge in machine learning because it requires jointly considering data, architecture, and training dy

A Thermodynamic Theory of Learning Part II: History-Dependent Reachability and Continual Learning

arXiv:2602.07950v3 Announce Type: replace Abstract: We formulate plasticity as target-dependent, finite-horizon reachability under history-dependent dynamics, using standard minimum-energy control the

A Transformer-Based Delta Expression Encoder for Psilocybin Transcriptional Response: Architecture, Representations, and Biological Validation

arXiv:2609.08165v1 Announce Type: cross Abstract: Understanding why individuals respond differently to psilocybin requires modeling the drug's transcriptional perturbation signature at the cell-type l

Accelerated High-Accuracy Sampling from a Warm Start via the Proximal Bouncy Particle Sampler

arXiv:2609.06905v1 Announce Type: cross Abstract: We study the problem of sampling from mu(dx)propto e^{-V(x)},dx on R^d, where V is alpha-strongly convex and eta-smooth, and write kappa:=eta/alpha. W

Accelerated Spatio-Temporal Gaussian Rendering via Kinematic and Semantic Priors

arXiv:2605.25909v2 Announce Type: replace Abstract: Reconstructing dynamic 3D scenes from multi-view videos is a foundational task for robotics, AR/VR, and digital twins. While 3D Gaussian Splatting (

Accelerating Diffusion Transformers with Gaussian Process Rectified Feature Cache

arXiv:2609.05981v1 Announce Type: new Abstract: Diffusion Transformers have become the dominant paradigm in generative AI, but their high computational costs severely hinder real-time applications. Pr

ActionSplice: In-Flight Action Editing for Interactive World Models

arXiv:2609.08230v1 Announce Type: new Abstract: Chunk-autoregressive video world models typically condition each generated chunk on one action. An action received during sampling must therefore wait f

Adapting Vision Foundation Models to Acoustics for Pose-Free 3D Sonar Reconstruction

arXiv:2609.06261v1 Announce Type: new Abstract: Vision foundation models trained on Internet-scale RGB datasets enable remarkable capabilities across a range of tasks, from text-to-video generation to

Adaptively Incorporating Directional Hints into Zeroth-Order Optimization

arXiv:2609.08277v1 Announce Type: new Abstract: We study zeroth-order optimization of non-convex functions with the aid of directional hints, which are cheap but potentially inaccurate approximations

AFID: A Unified Open Framework for Automated Fingermark Identification, Quality Assessment and Feature Extraction

arXiv:2609.07439v1 Announce Type: new Abstract: Automated fingermark identification is the foundation of forensic investigation, yet progress in the field is held back by fragmented, closed-source sol

AGSA-Net: Abundance-Guided Self-Attention Network for Spectral Unmixing-Aware Hyperspectral Remote Sensing Image Classification

arXiv:2609.06359v1 Announce Type: new Abstract: Hyperspectral image (HSI) classification plays a vital role in remote sensing applications, including agriculture, environmental monitoring, and urban a

Answer-Distribution Trajectories: A Stochastic-Dynamics View of LLM Reasoning

arXiv:2609.09030v1 Announce Type: cross Abstract: Chain-of-thought reasoning provides a structured computation between a model's input and final answer. Yet it is often evaluated through endpoint accu

Anti-Gravity Walking by a Flying Humanoid Robot via Thrust-Rate Input Whole-Body Model Predictive Control

arXiv:2609.07544v1 Announce Type: new Abstract: Flying humanoids are expected to perform tasks in diverse environments, while their existing locomotion is mainly limited to aerial flight and ground wa

Are Verifier Errors Independent Within a GRPO Group? Evidence from Qwen2.5 Rollouts

arXiv:2609.06386v1 Announce Type: new Abstract: Group-based reinforcement learning with verifiable rewards (RLVR) scoresmultiple completions per prompt using automatic verifiers. Analysesbased on inde

Attention-Enhanced Deep Features with Heterogeneous Ensemble Learning for Glaucoma Detection

arXiv:2609.06699v1 Announce Type: new Abstract: Glaucoma is a progressive optic neuropathy characterized by irreversible damage to the optic nerve, making timely diagnosis critical to prevent permanen

Attributing Cohen's d: Training Data Attribution for Disease-Related Effects in Normative Age Biomarkers

arXiv:2609.07729v1 Announce Type: new Abstract: Normative age models are trained to predict chronological age in a nominally healthy cohort. Applied to patients, they deviate, and the gap between pred

AVSplat: Dense-View Feed-Forward 3D Gaussian Splatting with Assist-View Preconditioning

arXiv:2609.05925v1 Announce Type: new Abstract: Pose-free feed-forward 3D Gaussian Splatting enables novel view synthesis from uncalibrated multi-view images. Although more views should improve perfor

AXS-Net: Interpretable Deep Unfolding for Hyperspectral Image Denoising via Spectral Basis Unmixing and Structured Noise Refinement

arXiv:2609.08777v1 Announce Type: new Abstract: Hyperspectral images (HSIs) are often degraded by mixed noise, including band-dependent Gaussian perturbations and structured artifacts such as stripes,

Bayesian Matrix-Valued Graphs for Context-Dependent Multivariate Relationships

arXiv:2609.08055v1 Announce Type: cross Abstract: Many scientific graphs attach several variables to each node, so a single scalar edge weight cannot describe direction-dependent interactions. We mode

Best-of-Both Worlds for linear contextual bandits with paid observations

arXiv:2510.07424v3 Announce Type: replace Abstract: We study linear contextual bandits with paid observations, where at each round the learner observes a context, selects an action, and may pay a fixe

Beyond Arbitrary Geometry: Topology Generalization In neural PDE Operators

arXiv:2609.05860v1 Announce Type: new Abstract: Neural operators that accept arbitrary meshes are often treated as geometry-general, but unseen domain topology changes both the invariant and decaying

Beyond Gait: Person Identification from Millimeter-Wave Point Clouds Across Activities of Daily Living

arXiv:2609.08818v1 Announce Type: new Abstract: Person identification from millimeter-wave (mmWave) point clouds has mainly relied on gait. Indoor walking, however, is often brief and interrupted, whi

Beyond Task Success: Stage-Wise Reliability of World Model Planning under Sensing Degradation

arXiv:2609.07126v1 Announce Type: cross Abstract: In world model planning, sensing inputs pass through an encoder and predictor before affecting planner decisions, so final task success alone cannot r

BIFTA: Brain-Inspired Few-Shot Tactile Adaptation for Unknown Sensors

arXiv:2609.08673v1 Announce Type: new Abstract: Advances in tactile sensing have made contact-rich perception possible, accelerating progress in robotic manipulation, material understanding, and embod

Boundary Voting Network for Ambiguity-Aware Timestamp-Supervised Action Segmentation

arXiv:2609.08167v1 Announce Type: new Abstract: Timestamp-supervised action segmentation aims to segment and classify actions in untrimmed videos with a random frame annotated per action. Precisely lo

BoundarySeg:Boundary-Aware Multi-Task Learning for Semi-Supervised 3D Medical Image Segmentation with Limited Unlabeled Data

arXiv:2505.09829v2 Announce Type: replace Abstract: Data scarcity is a primary bottleneck in 3D medical image segmentation: expert voxel-level annotations are expensive, and privacy regulations often

Branch-Centric Tokenization and Test-Time Augmentation for Skeleton Generation

arXiv:2609.06218v1 Announce Type: new Abstract: Automatic skeleton generation involves predicting both joint positions and skeletal connectivity. However, existing approaches struggle to encode branch

Bundle Length Tradeoffs in Decentralized Multi-Robot Task Allocation Under Degraded Communications

arXiv:2609.06273v1 Announce Type: new Abstract: Bundle length B is commonly fixed when configuring multi-task multi-robot task allocation (MRTA) algorithms. MinSum and MinMax are known to favor differ

Calendar-SPCA: Interpretable Representation Learning for Multi-Periodic Electricity Consumption Profiles

arXiv:2609.06060v1 Announce Type: new Abstract: Long-term electricity-consumption profiles exhibit several simultaneous periodic structures, including daily, weekly, and annual cycles. This work intro

CAM: Question Answering on Entity-Centric Videos with Continuous Extraction and Adaptive Querying

arXiv:2609.06504v1 Announce Type: new Abstract: Memory facilitates question answering over long videos by extracting and retrieving facts to fit within the limited context windows of multimodal LLMs (

Can People Distinguish Human and AI Agency in Humanoid Teleoperation? A Preliminary Study of Agency Perception

arXiv:2609.06434v1 Announce Type: cross Abstract: Can people distinguish between human and AI agency in humanoid teleoperation? To explore this question, we developed extit{Ghost-in-the-Loop}, a teleo

Canonical Color as a Lens into Concept Decodability in Vision Encoders and VLMs

arXiv:2609.09124v1 Announce Type: new Abstract: Visual encoders construct a representation of the image input for Vision-Language models. How much conceptual, as opposed to immediately visible, inform

CAR-MIL: Counterfactual Attention Regularization for Multiple Instance Learning

arXiv:2609.08419v1 Announce Type: new Abstract: Multiple Instance Learning (MIL) is widely used for weakly supervised learning, particularly in digital pathology, where fine-grained annotations are co

CAROL: Context-Aware Online Learning for Fuzzer Scheduling

arXiv:2609.06772v1 Announce Type: cross Abstract: Ensemble fuzzing runs multiple fuzzers on a target while a scheduler allocates CPU time among them. Existing schedulers base these decisions on compac

Cascaded Diffusion Framework for Probabilistic Coarse-to-Fine Hand Pose Estimation

arXiv:2510.00527v2 Announce Type: replace Abstract: Deterministic models for 3D hand pose reconstruction, whether single-staged or cascaded, struggle with pose ambiguities caused by self-occlusions an

Causal DAG Identification for Count Data via Poisson Thinning Structural Equation Models

arXiv:2609.06098v1 Announce Type: cross Abstract: Count-valued variables arise in many scientific and applied settings, yet explicit structural models that allow full identification of causal DAGs fro

CausalChapter: Improving Long-Video Chaptering with Interventional Dependency Modeling

arXiv:2609.08686v1 Announce Type: new Abstract: Long-form instructional videos require automatic chaptering to support browsing, navigation, and knowledge access. Recent long-context language models c

Certain companies train their AIs to plagiarise work by unnamed scholars, extending an AI history permeated by plagiarism and misattribution…

Certain companies train their AIs to plagiarise work by unnamed scholars, extending an AI history permeated by plagiarism and misattributions. It started a long time ago. In the 1900s, the old method

researchdavid-ha--x

Certified Topological Interaction in Neural Representations: Class Disentanglement Is Mostly Pairwise

arXiv:2609.08561v1 Announce Type: new Abstract: Class disentanglement (the separation of a representation's class-conditional point clouds along depth and over training) is usually read off descriptiv

Characterizing Privacy Risks of Quantum Machine Learning with Emergent Quantum-Native Access

arXiv:2609.05702v1 Announce Type: cross Abstract: Quantum Machine Learning (QML) has shown rapid advances by utilizing quantum computing for machine learning tasks. Meanwhile, the privacy risks accomp

Clean Accuracy Does Not Guarantee Provenance Robustness: A Prospective Codec-Stress Evaluation of Audio Attribution

arXiv:2609.07981v1 Announce Type: cross Abstract: Audio provenance attribution - which system produced a synthetic utterance - is reported at near-ceiling accuracy on clean benchmarks, yet audio reach

Clinician-Friendly Foundation Models for Ophthalmic Image Diagnostics without Fine-Tuning or Technical Barriers

arXiv:2504.15928v3 Announce Type: replace Abstract: Artificial intelligence (AI) shows remarkable potential in medical imaging diagnostics, yet most current models require retraining when applied acro

Closed-Form of the Local Galactic Potential and Stellar Distribution Function from Gaia DR3

arXiv:2609.09011v1 Announce Type: cross Abstract: The local dark matter density determines the strength of the signal expected in direct-detection experiments, yet published estimates from stellar mot

CodeTD: Topology of Attention Detects Hallucinations in Code LLMs

arXiv:2609.07779v1 Announce Type: cross Abstract: As AI-code assistant tools become widespread, automatic assessment of the correctness of generated code becomes a significant challenge. Code LLMs are

Comparison of D-Wave Quantum Annealing and Gibbs Monte Carlo for Sampling from a Probability Distribution of a Restricted Boltzmann Machine

arXiv:2508.10228v3 Announce Type: replace Abstract: A local-valley (LV) centered approach to assessing the quality of sampling from Restricted Boltzmann Machines (RBMs) was applied to the latest gener