Search: “research”

Full-resolution MLPs Empower Medical Dense Prediction

arXiv:2311.16707v2 Announce Type: replace-cross Abstract: Dense prediction is a fundamental requirement for many medical vision tasks such as medical image restoration, registration, and segmentation.

Geometry-Aware Style Transfer in 3D Gaussian Splatting

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DGX agent

arXiv:2606.24144v1 Announce Type: new Abstract: In this paper, we present a novel geometry-aware style transfer framework for 3D Gaussian splatting (3DGS) that simultaneously transfers appearance attr

researcharxiv-cs-cv

24 Jun 2026

Geometry-Instructed Video Editing

arXiv:2606.24225v1 Announce Type: new Abstract: Object-level geometric edits, including translating, rotating, scaling, duplicating, or removing an object, are routine operations in digital content cr

Grad Detect: Gradient-Based Hallucination Detection in LLMs

arXiv:2606.24790v1 Announce Type: cross Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse tasks, yet they remain prone to generating hallucinations. Detec

Ground Then Rank: Revisiting Knowledge-Based VQA with Training-Free Entity Identification

arXiv:2606.23881v1 Announce Type: new Abstract: Knowledge-Based Visual Question Answering (KB-VQA) requires grounding visual queries to external knowledge beyond directly observable content in images.

Grounding Generative Policies in Physics: Optimization-Guided Diffusion for Robot Control

arXiv:2606.24208v1 Announce Type: new Abstract: Diffusion models sample effectively from high-dimensional, multimodal distributions, but their outputs may violate deployment constraints. For task-spac

researcharxiv-cs-ro

Hessian-augmented Supervised Learning for Hamilton-Jacobi-Bellman PDEs

arXiv:2606.23827v1 Announce Type: cross Abstract: A data-driven method is developed for approximating value functions in deterministic optimal control problems with nonlinear control-affine dynamics.

High-Fidelity Synthetic Transmission Electron Microscopy Image Generation Using Diffusion Probabilistic Models for Data-Limited Semiconductor Metrology

arXiv:2606.24817v1 Announce Type: new Abstract: Advanced semiconductor nodes drastically increased demand for Transmission Electron Microscopy (TEM), yet destructive sample preparation, slow imaging a

Hybrid Event Frame Sensors: Modeling, Calibration, and Simulation

arXiv:2511.18037v2 Announce Type: replace Abstract: Hybrid event-frame sensors integrate an Event Vision Sensor (EVS) and an Active Pixel Sensor (APS) within a single chip, combining the high dynamic

Impatient Bandits: Optimizing for the Long-Term Without Delay

arXiv:2501.07761v2 Announce Type: replace-cross Abstract: Increasingly, recommender systems are tasked with improving users' long-term satisfaction. In this context, we study a content exploration tas

Importance of Intent-Sharing for V2X-based Maneuver Coordination

arXiv:2606.24203v1 Announce Type: cross Abstract: This paper examines the critical role of intent-sharing in enabling effective maneuver coordination for connected and automated vehicles (CAVs). Succe

researcharxiv-cs-ro

Infinitesimal Causality

arXiv:2606.24621v1 Announce Type: cross Abstract: This paper introduces a categorical account of infinitesimal causality in Frobenius Markov categories equipped with tangent-bundle semantics. IDC capt

Information-Theoretic Classifier-Free Guidance with Adaptive Schedule Optimization

arXiv:2606.24025v1 Announce Type: new Abstract: Diffusion models have achieved strong performance in image, text-to-image, and video generation, where conditional generation is often controlled by cla

Ingredient-Level Food Image Segmentation for Nutrition Awareness

arXiv:2606.24059v1 Announce Type: new Abstract: Food images often contain several visible ingredients, so assigning one dish label to an entire image hides important visual structure. This work studie

Integrated Sensing and Communications for Real-time Avatar Control in XR over 5G

arXiv:2606.23771v1 Announce Type: cross Abstract: Extended Reality (XR) presents a challenging use case for 5G and 6G networks, requiring high data-rates and lowlatency communication to deliver a trul

It's Complicated: On the Design and Evaluation of AI-Powered AAC Interfaces

arXiv:2606.24854v1 Announce Type: cross Abstract: Artificial intelligence (AI) can enhance what people who use augmentative and alternative communication (AAC) are able to do with their systems. Howev

JupOtter: Cell-Level Bug Detection in Jupyter Notebooks

arXiv:2606.23877v1 Announce Type: cross Abstract: Jupyter Notebooks are an increasingly popular coding environment used across many domains, especially in Python-based data science and scientific comp

Layer-wise Probing of wav2vec 2.0 and Whisper for Consonant Cluster Reduction in African American English

arXiv:2606.23948v1 Announce Type: new Abstract: Self-supervised and supervised speech models are increasingly used to investigate which linguistic information their internal representations encode, an

Model Releases

Legal Reasoning Is Not Lawyering: Rethinking Legal Benchmarks for Pro Se Access to Justice

model-releasesarxiv-cs-ai

arXiv:2606.23716v1 Announce Type: cross Abstract: Legal AI benchmark research frequently invokes the assumption that large language models can improve access to justice, including for people who canno

LLM-MINE: Large Language Model based Alzheimer's Disease and Related Dementias Phenotypes Mining from Clinical Notes

arXiv:2603.13673v2 Announce Type: replace Abstract: Accurate extraction of Alzheimer's Disease and Related Dementias (ADRD) phenotypes from electronic health records (EHR) is critical for early-stage

LLMs are Bayesian, In Expectation, Not in Realization

arXiv:2507.11768v3 Announce Type: replace-cross Abstract: Bayesian accounts of in-context learning face a direct objection: exact posterior predictives for exchangeable data are invariant to task-pres

M^2C-EvDet: Multi-Domain Multi-Order Cross-Modal Knowledge Distillation for Event-based Object Detection

arXiv:2606.24248v1 Announce Type: new Abstract: Event-based object Detection (EvDet), as a biologically inspired visual perception paradigm, demonstrates superior performance in scenarios demanding hi

Machine Learning Classification and Portfolio Construction: Does the Loss Function Matter?

arXiv:2108.02283v3 Announce Type: replace-cross Abstract: Classification outperforms regression across matched machine learning models in portfolio construction. A stacking ensemble of gradient booste

Maestro Order: A Model-Agnostic Orchestration Harness

arXiv:2606.23983v1 Announce Type: cross Abstract: A single forward pass of a capable model is a fast, fluent, and unreliable problem-solver: it is right often enough to be useful and wrong often enoug

Matching Tasks to Objectives: Fine-Tuning and Prompt-Tuning Strategies for Encoder-Decoder Pre-trained Language Models

arXiv:2606.24841v1 Announce Type: new Abstract: Prompt-based learning has emerged as a dominant paradigm in natural language processing. This study explores the impact of diverse pre-training objectiv

Measuring User's Mental Models of Speech Translation in Human-AI Collaboration

arXiv:2606.24644v1 Announce Type: new Abstract: Millions of people use machine translation (MT) tools daily, yet little is known about their perception of what systems can and cannot do. This paper st

MedPCFM: Improving Medical Point Cloud Completion by Integrating Point Transformers and Flow Matching

arXiv:2606.24433v1 Announce Type: cross Abstract: Medical point cloud completion is important for anatomical reconstruction and downstream clinical workflows, yet generative modeling in this setting r

Meet UD_Czech-PDTC: A Large and Genre-Rich Treebank in Universal Dependencies

arXiv:2606.24337v1 Announce Type: new Abstract: Czech has been part of Universal Dependencies since its first release in 2015. It has also been one of the best represented languages, with the Prague D

MERGE: Minimal Expression-Replacement GEneralization Test for Natural Language Inference

arXiv:2510.24295v2 Announce Type: replace Abstract: As many benchmarks have become saturated, it has become increasingly important to create new datasets that evaluate the generalization capacity of c

MGI: Member vs Generated Inference

arXiv:2606.23872v1 Announce Type: cross Abstract: As generative models increasingly produce samples that are indistinguishable from human-created content, it becomes difficult to determine whether a g

Minimisation of Quasar-Convex Functions Using Random Zeroth-Order Oracles

arXiv:2505.02281v3 Announce Type: replace-cross Abstract: This paper explores the performance of a random Gaussian smoothing zeroth-order (ZO) scheme for minimising quasar-convex (QC) and strongly qua

Model selection with proper scoring rules on data sets of time series

arXiv:2606.24715v1 Announce Type: cross Abstract: We consider the problem of model selection between probabilistic models on data sets of time series. Chosen a proper scoring rule, we denote by the te

ModTGCN: Modularity-aware Graph Neural Networks for Text Classification

arXiv:2606.23694v1 Announce Type: new Abstract: Graph-based text classification models typically rely on local neighborhood aggregation and overlook global community structure, despite semantic docume

MorfFlex: Handling Rich Morphology

arXiv:2606.24366v1 Announce Type: new Abstract: We present MorfFlex, a morphological dictionary architecture suitable for languages with extensive regularity in both inflection and derivation. As the

MorVess: Morphology-Aware Pulmonary Vessel Segmentation Network

arXiv:2606.24214v1 Announce Type: new Abstract: Accurate pulmonary vessel segmentation remains challenging due to the sparse, tortuous, and multi-scale nature of vascular structures, where small branc

MotifGen: Spatiotemporal interpolation of misaligned satellite images via multi-source generative modeling, in an application to tropical cyclones

arXiv:2606.24263v1 Announce Type: new Abstract: Microwave satellite imagery plays a crucial role in monitoring tropical cyclone precipitation and intensity worldwide, but suffers from long revisit tim

Multilevel Stochastic Plug-and-Play for Sparse-View CT Reconstruction

arXiv:2606.24567v1 Announce Type: new Abstract: Sparse-view computed tomography (SVCT) reduces radiation exposure and acquisition time, but the limited number of projection views makes the reconstruct

MuTRAP: Multi-trigger Trojans Attacking Robot Task Planning Systems

arXiv:2504.17070v3 Announce Type: replace-cross Abstract: Robots need task planning methods to achieve goals that require more than one action. Recently, large pretrained models have demonstrated impr

NeuroSonic: Conditional Flow Matching for EEG-to-Speech Reconstruction

arXiv:2606.24087v1 Announce Type: new Abstract: Reconstructing continuous speech from scalp electroencephalography (EEG) remains fundamentally challenging. EEG provides a weak, spatially diffuse, and

New Bounds for the Last Iterate of the Stochastic subGradient Method

arXiv:2606.24879v1 Announce Type: cross Abstract: We study the last iterate of the stochastic subgradient method for one-dimensional convex Lipschitz objectives. For a fixed horizon n, we consider the

OrbitForge: Text-to-3D Scene Generation via Reconstruction-Anchored Video Synthesis

arXiv:2606.24799v1 Announce Type: cross Abstract: Generic text-to-video models can be used as rich open-world scene priors. Despite the high quality of today's generated videos, they do not directly y

P-MTP: Efficient Document Parsing via Multi-Token Prediction with Progressive Depth Scaling

arXiv:2606.24447v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have revolutionized document parsing by enabling end-to-end mapping from images to structured text, imposing a significant

Parallel Manifold Steering: Efficient Adaptation of Large Associative Memories via Residual Energy Shaping

arXiv:2606.24396v1 Announce Type: new Abstract: Large Transformer models function as Dense Associative Memories (DAMs), retrieving knowledge via high-dimensional attractor dynamics driven by the self-

Pigeonholing: Bad prompts hurt models to collapse and make mistakes

arXiv:2606.24267v1 Announce Type: cross Abstract: While in-context learning is generally shown to be effective in Large Language Models (LLMs), bad contexts can cause performance degradation and mode

PORTER: Language-Grounded Event Representations for Portable Structured EHR Foundation Models

arXiv:2606.24102v1 Announce Type: new Abstract: Most electronic health record (EHR) foundation models encode clinical events as discrete event tokens from a fixed vocabulary and therefore cannot direc

Posterior Refinement: Fast Language Generation via Any-Order Flow Maps

arXiv:2606.24773v1 Announce Type: new Abstract: Non-autoregressive generation offers a powerful paradigm for iterative refinement, allowing models to recursively critique, erase and regenerate arbitra

Posterior Sampling Reinforcement Learning with Gaussian Processes for Continuous Control: Sublinear Regret Bounds for Unbounded State Spaces

arXiv:2603.08287v2 Announce Type: replace-cross Abstract: We analyze the Bayesian regret of the Gaussian process posterior sampling reinforcement learning (GP-PSRL) algorithm. Posterior sampling is a

Predicting brain tumour enhancement from non-contrast MR imaging with artificial intelligence: a multi-cohort retrospective diagnostic accuracy study

arXiv:2508.16650v3 Announce Type: replace-cross Abstract: Brain tumour MRI typically requires both pre- and post-contrast imaging, but gadolinium is not always desirable (frequent follow-up, renal imp