Search: “research”

MARS-CLIP: Multi-Resolution and Attention Refined Zero-Shot Image Segmentation

arXiv:2609.08283v1 Announce Type: new Abstract: Contrastive Language-Image Pre-training (CLIP) has demonstrated impressive capabilities in zero-shot transfer but often struggles with dense prediction

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Mask Forcing: Improving Autoregressive Video Diffusion Distillation via Dual-Noise Masking Rollout

DGX agent

arXiv:2609.09123v1 Announce Type: new Abstract: Autoregressive (AR) video diffusion models have shown great potential in real-time video generation. Recent methods distill pretrained bidirectional vid

researcharxiv-cs-cv

9 Sept 2026

Matryoshka Hash Representations for Model-Aware Compact Semantic Retrieval

arXiv:2609.07276v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) depends on dense retrieval: each document is stored as a learned vector, and a query is answered by finding its n

MCANet: A Multi-Scale Class-Specific Attention Network for Multi-Label Post-Hurricane Damage Assessment Using UAV Imagery

arXiv:2509.04757v2 Announce Type: replace Abstract: Hurricanes cause widespread damage to buildings, roads, and other infrastructure, making timely post-disaster damage assessment critical for emergen

MedGround: Bridging the Evidence Gap in Medical Vision-Language Models with Verified Grounding Data

arXiv:2601.06847v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) can generate convincing clinical narratives, yet frequently struggle to visually ground their statements. We posit tha

Medical AI Encodes a 'Feeling of Error': Verifying Cancer Segmentation via Internal Concepts

arXiv:2609.08879v1 Announce Type: new Abstract: Cancer segmentation models can fail silently, generating plausible but incorrect masks that risk missed findings or unnecessary biopsies. A critical que

MetaKV: Adaptive KV Cache Compression for Constrained LLM Inference

arXiv:2609.07966v1 Announce Type: new Abstract: Key--value (KV) cache compression is an effective way to reduce the memory overhead of large language model (LLM) inference, particularly for long-conte

MFVINS: Multiple Fisheye Camera-Based Visual Inertial System

arXiv:2609.08626v1 Announce Type: cross Abstract: A simultaneous localization and mapping (SLAM) method using a monocular camera and a low-cost inertial measurement unit (IMU) sensor is an effective w

MGD: Moment Guided Diffusion for Maximum Entropy Generation

arXiv:2602.17211v2 Announce Type: replace-cross Abstract: Generating samples from limited information is a fundamental problem across scientific domains. Classical maximum entropy methods provide prin

MILAAP: Mobile Link Allocation via Attention-based Prediction

arXiv:2506.19947v2 Announce Type: replace-cross Abstract: Channel hopping (CS) communication systems must adapt to interference changes in the wireless network and to node mobility for maintaining thr

Mind the Gap: Navigating Inference with Optimal Transport Maps

arXiv:2507.08867v3 Announce Type: replace-cross Abstract: Machine learning (ML) techniques have recently enabled enormous gains in sensitivity to new phenomena across the sciences. In particle physics

Mind-to-Face: Neural-Driven Photorealistic Avatar Synthesis via EEG Decoding

arXiv:2512.04313v2 Announce Type: replace Abstract: Current expressive avatar systems rely heavily on visual cues, failing when faces are occluded or when emotions remain internal. We present Mind-to-

Minimum distance classification for nonlinear dynamical systems

arXiv:2601.04058v3 Announce Type: replace Abstract: We address the problem of classifying trajectories or sequences generated by nonlinear dynamical systems, where each class corresponds to a distinct

MM-SVGEdit: A Multimodal-Driven SVG Editing for UI Design

arXiv:2609.06116v1 Announce Type: cross Abstract: In the field of UI design, Scalable Vector Graphics (SVG) is widely used as a design medium. However, traditional SVG editing techniques have high ent

MoEMB: Scaling Universal Multimodal Embeddings with Efficient Mixture-of-Experts Models

arXiv:2609.08663v1 Announce Type: new Abstract: Universal multimodal embedding (UME) increasingly demands encoder's capacity for handling a broad range of tasks and modalities with increased complexit

MORPHA: Morphology-Constrained Training and the Limits of Cross-Acquisition Transfer in Low-Resource Malaria Microscopy

arXiv:2609.05990v1 Announce Type: new Abstract: In low-resource malaria microscopy, a model trained on one smear preparation routinely meets images from another, and how well morphology-based constrai

Multi-bounce Drum Roll with Optimized Active Tricks to Leverage Soft Embodiment

arXiv:2609.08490v1 Announce Type: new Abstract: This paper presents a soft robotic drummer for accurate and efficient drum rolls. High-frequency drum rolls require the 'multi-bounce technique,' where

researcharxiv-cs-ro

Multi-History-Step SDE Inversion for Image Editing with Superior Regional Awareness

arXiv:2609.06602v1 Announce Type: new Abstract: In recent years, diffusion stochastic differential equation (SDE) inversion and inversion-free methods have become prevalent for training-free image edi

Multi-label versus multi-class classification of blood cells and their aggregates in microfluidic channels

arXiv:2609.07410v1 Announce Type: new Abstract: Deformability cytometry (DC) is a type of imaging flow cytometry, which uses a camera-equipped device to measure cellular stiffness in addition to other

Multimodal Resource-Exhaustion Attacks on Vision-Language Models via Joint Pixel-Prompt Optimization

arXiv:2609.05889v1 Announce Type: cross Abstract: Resource-exhaustion attacks against autoregressive vision-language models (VLMs) typically assume unimodal threat models, treating the image branch as

Multiple Myeloma Lesion Segmentation on Whole-Body Diffusion-Weighted Imaging via Efficient Anatomical Anticipation and Multimodal Confirmation

arXiv:2609.06165v1 Announce Type: new Abstract: Whole-body diffusion-weighted imaging (WB-DWI) is widely used for multiple myeloma (MM) assessment, yet automated lesion segmentation remains challengin

MV-STRIDE: Enabling MLLMs to Master Multi-View Spatial Reasoning via Hierarchical Capability Modeling

arXiv:2609.07258v1 Announce Type: new Abstract: Despite the rapid progress of Multimodal Large Language Models (MLLMs) in 2D vision-language tasks, robust multi-view spatial reasoning remains a fundam

Neither Adversarial Training Nor Purification: Emergent Adversarial Robustness from Oscillatory Predictive Learning

arXiv:2609.08683v1 Announce Type: new Abstract: Adversarial robustness in computer vision is still largely achieved through adversarial training or test-time adversarial purification, both of which in

Neural Posterior Estimation for Tomographic Weak Lensing Mass Mapping

arXiv:2609.07833v1 Announce Type: cross Abstract: Weak gravitational lensing shear and convergence trace the distribution of baryonic and dark matter across space, making them a powerful probe of cosm

Newton Matching for Generative Modeling: A Unified Framework for Fine-Tuning and Sampling

arXiv:2609.05727v1 Announce Type: new Abstract: We develop Newton Matching, a unified framework for fine-tuning and sampling in generative modeling. The target is piproptomu e^{au r}, where r is the r

NoLoCo: No-all-reduce Low Communication Training Method for Large Models

arXiv:2506.10911v2 Announce Type: replace Abstract: Training large language models is generally done on clusters containing thousands of accelerators, communicating over a high-bandwidth interconnect.

Nonlinear elliptic homogenization with the parametric Deep Ritz method

arXiv:2609.05778v1 Announce Type: new Abstract: Elliptic homogenization is used to determine coarse-grained properties of materials with features on small scales. When these small scale features have

Not All Variables Agree: Reliability-Aware Variable-Wise Gradient Surgery for Multivariate Time-Series Forecasting

arXiv:2609.08554v1 Announce Type: new Abstract: In data-driven training, multivariate time-series forecasting is usually optimized with a scalar loss averaged over samples, variables, and horizons. Th

NSFlow: End-to-End Differentiable Neuro-Symbolic Optical Flow for Visual Odometry

arXiv:2609.06074v1 Announce Type: new Abstract: Sparse optical flow provides stable inter-frame correspondence, playing a key role in Visual Odometry (VO) and Visual-Inertial Odometry (VIO). Classical

Nystrom Attention Matches Full Attention for Cross-Sectional Stock Prediction

arXiv:2609.08106v1 Announce Type: new Abstract: MASTER's inter-stock multi-head attention -- the module responsible for modeling cross-sectional stock relationships -- accounts for 42.5% of model para

Observation Design for Certified Control Authority: Projection--Estimability Separation and Active-Face Equivalence

arXiv:2609.05962v1 Announce Type: new Abstract: A sound runtime admission gate executes only actions it can certify, and certifies only what its observations support. This paper asks how observations

researcharxiv-cs-ro

On BatchNorm Forward Modes in Value-Based Reinforcement Learning

arXiv:2609.06421v1 Announce Type: new Abstract: Batch normalization (BN) substantially improves sample efficiency in continuous-control actor-critic methods such as CrossQ, yet recent studies report p

On Generalisation Error Bounds for Transformers

arXiv:2410.11500v2 Announce Type: replace-cross Abstract: In this paper, we establish a collection of covering number bounds for linear function classes under various norm constraints on the inputs an

On the Effectiveness of the z-Transform Method in Quadratic Optimization

arXiv:2507.03404v3 Announce Type: replace Abstract: The z-transform of a sequence is a classical tool used within signal processing, control theory, computer science, and electrical engineering. It al

One for All: Generalist Foundation Model for Cross-Sensor Skeleton Representation Learning

arXiv:2609.07078v1 Announce Type: new Abstract: For learning generalizable motion representations from large-scale unlabeled data, Self-supervised learning (SSL) has become a widely adopted methodolog

One Model, Two Worlds: Bidirectional Sonar-Optical Translation

arXiv:2609.06253v1 Announce Type: new Abstract: Translating between imaging sonar and optical cameras is valuable for underwater perception, but supporting both directions with separate models duplica

Open-Set Ego-Noise Separation for Legged-Robot Audition via Annotation-Free Adaptation and Pretrained-Model Transfer

arXiv:2609.07440v1 Announce Type: new Abstract: This paper proposes an open-set ego-noise separation framework for legged-robot audition via annotation-free adaptation and pretrained-model transfer. T

researcharxiv-cs-ro

Optimal estimation for Functional Linear Regression with Noisy Discretized Data

arXiv:2609.08671v1 Announce Type: cross Abstract: In this paper, we consider the scalar-on-function linear regression model under a realistic sampling scheme in which the functional covariates are obs

Optimal Slice-Adaptive Tuning of Hybrid Slice Sampling

arXiv:2609.08172v1 Announce Type: cross Abstract: Slice sampling is a Markov chain Monte Carlo algorithm that draws its next state uniformly from a 'slice'---a super-level set of the target density fu

PAC-Private Autoregressive Generation: Calibrating Noise to Ensemble Disagreement

arXiv:2609.05676v1 Announce Type: new Abstract: Language models adapted on private text are often served through APIs, so privacy leakage occurs through generated outputs rather than exposed weights.

Parser-Free VLM Verification for Federated Weakly Supervised Video Anomaly Detection

arXiv:2609.07455v1 Announce Type: new Abstract: How can vision-language models help video anomaly detection (VAD) when surveillance data remain distributed, weakly labeled, and resource-constrained? M

Particle Dynamics of Flow Matching and Classifier-Free Guidance from a Stagewise Geometry Perspective

arXiv:2609.06947v1 Announce Type: new Abstract: Flow matching, together with classifier-free guidance (CFG), is widely used in generative modeling, yet much of the theoretical understanding remains di

Patient-Specific Articulated Digital Twins from a Single Full-Body CT Scan

arXiv:2607.02156v2 Announce Type: replace Abstract: Patient-specific anatomical models provide individualized context for surgical planning, image-guided intervention, and algorithm development. Howev

PCFlow: Physics-Conditioned Flow Matching for GPR B-Scan Image Synthesis

arXiv:2609.07300v1 Announce Type: new Abstract: Ground-penetrating radar (GPR) B-scan image synthesis is important for data augmentation, algorithm validation, and simulation acceleration, yet generat

Physico-Geospatial Grounded Scene Interpretation for Mobile Robotics

arXiv:2609.06629v1 Announce Type: new Abstract: Recent advancements in deep learning allow robotic agents to interact with dynamic and unstructured environments. Of special interest is the integration

Physics-Informed Neural Networks for Depth-Averaged Granular Avalanche Dynamics on Curved Topography

arXiv:2609.05542v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) provide a mesh-free framework for solving governing equations, but their application to granular avalanche dy

PhysSAE: Mechanistic Interpretability with Sparse Autoencoders

arXiv:2609.07061v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) embed PDE residuals into neural network training, but their internal representations remain opaque: it is unkno

PIC: Revisiting INR for Image Coding with Fast Encoding and Sub-Millisecond Decoding

arXiv:2609.09020v1 Announce Type: new Abstract: Implicit neural representation (INR) has achieved remarkable progress in novel view synthesis and image/video coding in recent years.Compared to convent