research

Dense-Cast: A lightweight ensemble of deep learning architectures for precipitation nowcasting

arXiv:2608.06082v1 Announce Type: new Abstract: Proper short-term forecasting of precipitation is crucial in disaster management and preparedness. Nonetheless, the variability and nonlinearity of prec

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Depth-Guided Video Object Counting in Crowded Scenes

DGX agent

arXiv:2608.06236v1 Announce Type: cross Abstract: Our primary objective is to advance video object counting in crowded scenes, aiming to robustly count all instances of a target category based on give

researcharxiv-cs-ai

7 Aug 2026

Diff-VF: Training-free High-quality Long Video Generation via Diffusion Model

arXiv:2608.05976v1 Announce Type: new Abstract: Recently, diffusion models have made great progress in video generation. However, most existing video diffusion models are trained with short videos, an

Discrete energy as an exact label-free training objective for finite-element surrogates

arXiv:2608.05437v1 Announce Type: cross Abstract: Supervised training of finite-element (FE) surrogate models requires reference solutions, and each reference solution is obtained by solving the syste

Does FLAIR super-resolution erase or hallucinate small white-matter lesions?

arXiv:2608.06311v1 Announce Type: cross Abstract: White matter hyperintensities (WMH), bright regions on Fluid-attenuated Inversion Recovery (FLAIR) scans are associated with cerebrovascular pathology

Dual-Output Multi-Exposure HDR Reconstruction via SDR Fusion and Gain Map Inverse Tone Mapping

arXiv:2608.05626v1 Announce Type: new Abstract: We propose DOME-HDR, a dual-output multi-exposure HDR reconstruction framework that jointly produces a perceptually balanced SDR image and a consistent

Engram-E2VID: Reference-Based Event-to-Video Reconstruction via Generative Activation of Appearance Engrams

arXiv:2608.05728v1 Announce Type: new Abstract: Reference-based event-to-video reconstruction aims to recover target RGB frames from a reference frame and the event stream captured over the reference-

EqDeepRx: Learning a Scalable and Interference Mitigating MIMO Receiver

arXiv:2602.11834v2 Announce Type: replace-cross Abstract: While machine learning (ML)-based receiver algorithms have received a great deal of attention in the recent literature, they often suffer from

Equipment-centric workpiece localization in near real-time using deep learning-based vision and event-driven finite state machines

arXiv:2608.05744v1 Announce Type: new Abstract: Continuous workpiece localization is essential for traceability and process coordination in hot forging, but direct tracking is unreliable because of ex

Evaluating Machine Learning Models for Post-Wildfire Debris-Flow Prediction

arXiv:2608.05265v1 Announce Type: cross Abstract: Prediction of post-wildfire debris flows is critical for mitigating hazards to communities, infrastructure, and resources during intense rainfall in r

Example-Guided Prompting for Document-Level Text Simplification

arXiv:2608.05447v1 Announce Type: new Abstract: Document-level text simplification requires large language models (LLMs) to rewrite complex documents while preserving meaning, readability, and discour

researcharxiv-cs-cl

Flow-Map Distillation on Relation Manifolds for Image Restoration

arXiv:2608.05769v1 Announce Type: new Abstract: Knowledge distillation for image restoration typically aligns intermediate features or relation matrices between teacher and student networks as static

From Continuous Predictors to Clinical Thresholds: Early Evidence on Performance Trade-offs of Guideline-Based Categorisation for Ischaemic Stroke Outcome Prediction

arXiv:2608.05203v1 Announce Type: new Abstract: Machine learning models achieve strong predictive accuracy for 90-day outcome prediction in acute ischaemic stroke, yet clinical adoption is limited by

Gender-Based Heterogeneity in Youth Privacy-Protective Behavior for Smart Voice Assistants: Evidence from Multigroup PLS-SEM

arXiv:2603.27117v2 Announce Type: replace-cross Abstract: This paper investigates how gender shapes privacy decision-making in youth smart voice assistant (SVA) ecosystems. Using survey data from 469

Grad-CAM for Vision Transformers: A Systematic Taxonomy and Audit of Methodological Ambiguity in Explainable AI

arXiv:2608.05258v1 Announce Type: new Abstract: Gradient-weighted Class Activation Mapping (Grad-CAM) is widely used to visualize model decisions, but it was originally formulated for convolutional ne

HERA: Historical Evidence Routing Adapter for Physical Prediction in Latent World Models

arXiv:2608.05523v1 Announce Type: new Abstract: Predictive video models have emerged as promising world models by learning latent visual dynamics from large-scale video. Yet these models remain challe

Hierarchical Flow Matching for 3D Point Cloud Generation

arXiv:2608.05557v1 Announce Type: new Abstract: Generating high-quality 3D point clouds requires capturing both global shape topology and local geometric details. Existing flow-based methods rely on c

Hierarchical Latent Prediction for Language Models

arXiv:2608.05806v1 Announce Type: cross Abstract: While standard Next-Token Prediction (NTP) lays the foundation of language model pre- training, its teacher-forced training paradigm may not be optima

HOPE: Hand-Object Pressure Estimation from Monocular Videos

arXiv:2608.06192v1 Announce Type: new Abstract: Estimating physical pressure from vision is essential for understanding contact-rich hand-object interaction. However, prior vision-based pressure estim

How Far Do Simple Transformations Translate Across Text Embedding Models?

arXiv:2608.05980v1 Announce Type: new Abstract: We investigate whether simple transformations can translate representations across heterogeneous text embedding models. Understanding how independently

Hybrid Probabilistic Zonotopes for Identifiable and Refinable Predictive Uncertainty

arXiv:2608.05454v1 Announce Type: new Abstract: Probabilistic prediction heads in neural networks typically output either a Gaussian mixture or a single conformal region. Neither separates the distinc

HyTBE: Hyperbolic Target-Background Expert Model for Cross-Domain Infrared Small Target Detection

arXiv:2608.05771v1 Announce Type: cross Abstract: Infrared small target detection (IRSTD) has achieved substantial progress under domain-consistent evaluation, yet detector performance often degrades

I concur, and the point is broader than just for Biology. Science does not advance by 'pure thinking' alone. We need to do experiments, and …

I concur, and the point is broader than just for Biology. Science does not advance by 'pure thinking' alone. We need to do experiments, and interpret the results of those experiments, which in turn ra

researchyann-lecun--x

In the era of base LLM scaling (2022-2024), I believed the LLM line of research would reach a capability plateau (as later seen with base LL…

researchfrancois-chollet--x

In the era of base LLM scaling (2022-2024), I believed the LLM line of research would reach a capability plateau (as later seen with base LLMs). In late 2024, after the o3 test-time compute demo, I ch

Integrating Human Linguistic Insights into AI: Theory-Driven Representation for Multilingual Text-to-Speech

arXiv:2204.07228v2 Announce Type: replace Abstract: This paper explores the integration of human linguistic insights into multilingual text-to-speech (TTS) systems by evaluating the Featurally Undersp

researcharxiv-cs-cl

Invisible Shortcuts: Why Vision Encoders Know Your Camera

arXiv:2608.05424v1 Announce Type: new Abstract: Deep vision models exploit shortcuts, relying on cues that correlate with supervision signals. Prior work has focused on visible biases, such as object-

Is Self-Pretraining really useful to improve diagnosis in medical Time Series?

arXiv:2608.06122v1 Announce Type: cross Abstract: Inspired by recent evidence that transformer architectures benefit from Self-PreTraining (SPT) on long-context benchmarks, we investigate whether simi

KVAE: Family of Tokenizers for Multimodal Generative Models

arXiv:2608.05798v1 Announce Type: new Abstract: Latent diffusion modeling (LDM), a prominent paradigm, utilizes tokenizers to map input signal to compressed representation. This dependency positions t

LC-Implicit-QAOA: Active-Workspace-Capped Exact Objective-and-Gradient Evaluation for Training over Bounded QUBO Light Cones

arXiv:2608.05610v1 Announce Type: cross Abstract: QAOA training repeatedly queries an objective and all shared gradients, making exact evaluation a feasibility bottleneck even when QUBO terms have bou

Learning from Failures: Retrieval-Centric CoT via Hard Negatives for Unified Multimodal Retrieval

arXiv:2608.06060v1 Announce Type: new Abstract: Unified multimodal retrieval aims to identify candidates that satisfy complex user intent expressed through heterogeneous inputs. Although Large Vision-

LELA: an LLM-based Entity Linking Approach with Zero-Shot Domain Adaptation

arXiv:2601.05192v2 Announce Type: replace Abstract: Entity linking (mapping ambiguous mentions in text to entities in a knowledge base) is a foundational step in tasks such as knowledge graph construc

researcharxiv-cs-cl

LILAC: An Idempotent Neural Speech Codec

arXiv:2608.05727v1 Announce Type: cross Abstract: Neural Audio Codecs are widely adopted in speech generation and editing. However, existing neural audio codecs are not idempotent: across the paper's

Mapping Armenian Paris: Extracting and Geocoding Commercial Advertisements from the 20th-Century Diaspora Press

arXiv:2608.05911v1 Announce Type: new Abstract: This paper presents an end-to-end, IIIF-based pipeline that turns the digitised Armenian press of France into an interactive map of the 20th-century Par

MirrorNet: Can Medical Image Anonymization Really Protect Patient Identity?

arXiv:2608.05938v1 Announce Type: new Abstract: Medical images are routinely de-identified---names, dates, and other metadata removed---and then shared for research, teaching, and public benchmarks un

ML-for-ML

arXiv:2608.06046v1 Announce Type: cross Abstract: AI training workloads are growing rapidly, making their time, energy, and infrastructure costs increasingly important. In shared cloud clusters, train

MOSAIK: Multi-Patch Content-Aware Spatial Allocation of Image Tokens for Efficient Generation

arXiv:2608.05450v1 Announce Type: new Abstract: Pixel-space diffusion models avoid the reconstruction ceiling of latent diffusion models by generating directly in image space. However, their substanti

Multi-Year Geospatial Reasoning using Interannually-Consistent Historical Predictions as a Free Input Modality

arXiv:2608.05979v1 Announce Type: new Abstract: Machine learning, and deep networks in particular, are increasingly used to derive higher-level Earth observation (EO) products such as annual land-cove

Multivariate Time Series Forecasting needs Cross Variable Loss

arXiv:2608.05742v1 Announce Type: cross Abstract: Multivariate time series forecasting presents unique challenges because future variables often co-evolve under shared system dynamics. While existing

Muon on the Stiefel Manifold Admits an Exact Closed-Form Update

arXiv:2608.06218v1 Announce Type: cross Abstract: We study Muon, a recently proposed matrix-aware optimization method, in the context of the Stiefel manifold. This manifold consists of matrices with o

Near-sensor Computing for Rapid Visuotactile Perception

arXiv:2608.05725v1 Announce Type: new Abstract: Visuotactile sensors reconstruct dense contact geometry from measured surface gradients, but host-based processing increases power consumption and intro

researcharxiv-cs-ro

NeuroAdaptTrainer: A Fiji/ImageJ Plugin for YOLO-Based Neuron Segmentation, InteractiveCorrection and Transfer Learning

arXiv:2608.05226v1 Announce Type: new Abstract: Neuron counting and segmentation in microscopy images of neuronal cultures is a routine and time-consuming task in neuroscience research, traditionally

On Same-Sample and Independent-Sample Stochastic Extragradient for Monotone Variational Inequalities

arXiv:2608.06182v1 Announce Type: cross Abstract: We study stochastic extragradient (SEG) methods for solving monotone variational inequality problems (VIPs) over a feasible set. Although extragradien

On the Anisotropy of Score-Based Generative Models

arXiv:2510.22899v2 Announce Type: replace Abstract: We investigate the role of network architecture in shaping the inductive biases of modern score-based generative models. To this end, we introduce t

Once a Response, Always a Response: Detecting LLM-generated Text via Latent Prompt Restoration

arXiv:2608.05741v1 Announce Type: cross Abstract: Large language models (LLMs) can generate fluent and convincing text at scale, creating growing risks for misinformation dissemination, educational mi

One Qubit Can Beat One Bit: Quantum Advantage for Post-Training Quantization

arXiv:2608.05240v1 Announce Type: cross Abstract: One-bit post-training quantization represents each weight using only its sign, requiring all deployment contexts to share the same binary weight matri

One Ranking, Any Budget: Matryoshka Evidence-to-Context Frame Selection for Long-Video Understanding

arXiv:2608.05707v1 Announce Type: new Abstract: Frame selection is essential for applying Large Multimodal Models (LMMs) to long videos due to severe frame redundancy and limited context windows. Sinc

Online Reasoning Calibration: Test-Time Training Enables Generalizable Conformal LLM Reasoning

arXiv:2604.01170v2 Announce Type: replace-cross Abstract: While test-time scaling has enabled large language models to solve highly difficult tasks, state-of-the-art results come at exorbitant compute

Optimal or Greedy Decision Trees? Revisiting their Objectives, Tuning, and Performance

arXiv:2409.12788v3 Announce Type: replace Abstract: Recently there has been a surge of interest in optimal decision tree (ODT) methods that globally optimize accuracy directly, in contrast to traditio