Search: “research”

VISTA: Triplet-Supervised Video Style Transfer with Diffusion Transformers

arXiv:2605.17312v1 Announce Type: new Abstract: Video style transfer aims to render videos in a target artistic style while preserving content, structure, and motion. While image stylization has advan

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Visual Search Patterns in 3D Pancreatic Imaging: An Eye Tracking Study

DGX agent

arXiv:2605.16408v1 Announce Type: new Abstract: Eye tracking has emerged as a powerful tool for examining visual perception and search strategies in various domains, including medicine. While it is re

researcharxiv-cs-cv

19 May 2026

Visual Timelines of Police Encounters in Body-Worn Camera Footage: Operational Context and Activity Cataloging for Training and Analysis in OpenBWC

arXiv:2605.17095v1 Announce Type: cross Abstract: Law enforcement agencies are accumulating vast amounts of body-worn camera (BWC) footage. However, this remains operationally opaque. That is, analyst

Voice ''Cloning'' is Style Transfer

arXiv:2605.16578v1 Announce Type: cross Abstract: Artificially generated speech is increasingly embedded in everyday life. Voice cloning in particular enables applications where identity preservation

VoxScene: Anchor-Conditioned Voxel Diffusion for Indoor Scene Arrangement

arXiv:2605.17102v1 Announce Type: cross Abstract: We present VoxScene, a novel anchor-conditioned voxel diffusion framework tailored for 3D scene synthesis. Current data-driven layout generation techn

WASIL: In-the-Wild Arabic Spoken Interactions with LLMs

arXiv:2605.16364v1 Announce Type: cross Abstract: Large Language Models (LLMs) voice assistants are commonly built as cascaded Automatic Speech recognition (ASR) to LLM systems, where recognition erro

Wasserstein bounds for denoising diffusion probabilistic models via the Follmer process

arXiv:2605.18069v1 Announce Type: cross Abstract: This paper studies sampling error bounds for denoising diffusion probabilistic models (DDPMs) in the 2-Wasserstein distance. Our contributions are thr

Wavelet Flow Matching for Multi-Scale Physics Emulation

arXiv:2605.16573v1 Announce Type: cross Abstract: Accurate emulation of multi-scale physical systems governed by PDEs demands models that remain stable over long autoregressive rollouts while preservi

Weighted Reverse Convolution for Feature Upsampling

arXiv:2605.17472v1 Announce Type: new Abstract: Pre-trained vision foundation models (VFMs) provide strong semantic representations, yet their patch-level features are inherently coarse, limiting thei

Weisfeiler and Leman Follow the Arrow of Time: Expressive Power of Message Passing in Temporal Event Graphs

arXiv:2505.24438v3 Announce Type: replace Abstract: An important characteristic of temporal graphs is how the directed arrow of time influences their causal topology, i.e., which nodes can possibly in

What is Holding Back Latent Visual Reasoning?

arXiv:2605.18445v1 Announce Type: cross Abstract: Humans can approach complex visual problems by mentally simulating intermediate visual steps, rather than reasoning through language alone. Inspired b

What is the long-run distribution of stochastic gradient descent? A large deviations analysis

arXiv:2406.09241v3 Announce Type: replace-cross Abstract: In this paper, we examine the long-run distribution of stochastic gradient descent (SGD) in general, non-convex problems. Specifically, we see

What Matters for Grocery Product Retrieval with Open Source Vision Language Models

arXiv:2605.18029v1 Announce Type: new Abstract: Multimodal product retrieval (MPR) underpins checkout-free retail and automated inventory systems, yet it demands fine-grained SKU discrimination that s

When a Zero-Shooter Cheats: Improving Age Estimation via Activation Steering

arXiv:2605.17658v1 Announce Type: new Abstract: Different age-related regulations have been proposed to protect minors from harmful content and interactions online. Automated age estimation is central

When Bits Break Recourse: Counterfactual-Faithful Quantization

arXiv:2605.17160v1 Announce Type: cross Abstract: Quantization can preserve predictive accuracy under low-bit deployment while silently breaking algorithmic recourse: an actionable change that flips a

When Efficiency Backfires: Cascading LLMs Trigger Cascade Failure under Adversarial Attack

arXiv:2605.17288v1 Announce Type: cross Abstract: Large Language Model (LLM) cascade systems are designed to balance efficiency and performance by processing queries with lightweight models while sele

When Fireflies Cluster; Enhancing Automatic Clustering via Centroid-Guided Firefly Optimization

arXiv:2605.18460v1 Announce Type: new Abstract: This work presents a novel variant of the Firefly Algorithm (FA) for data clustering, addressing limitations of traditional methods like K-Means that st

When Marginals Match but Structure Fails: Covariance Fidelity in Generative Models

arXiv:2603.17041v2 Announce Type: replace-cross Abstract: Generative models are increasingly deployed as substitutes for real data in downstream scientific workflows, yet standard evaluation criteria

Why Do Reasoning Models Lose Coverage? The Role of Data and Forks in the Road

arXiv:2605.17026v1 Announce Type: new Abstract: Recent progress in large language models has led to the emergence of reasoning models, which have shown strong performance on complex tasks through spec

WinQ: Accelerating Quantization-Aware Training of Language Models Around Saddle Points

arXiv:2605.17471v1 Announce Type: new Abstract: Quantization-aware training (QAT) is widely adopted to quantize language models by training full-precision weights using gradients from the quantized mo

You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations

arXiv:2511.06516v3 Announce Type: replace Abstract: Many LLM applications require only narrow capabilities, yet standard post-training quantization (PTQ) methods allocate precision without considering

researcharxiv-cs-cl

2Mamba2Furious: Linear in Complexity, Competitive in Accuracy

arXiv:2602.17363v3 Announce Type: replace Abstract: Linear attention transformers have become a strong alternative to softmax attention due to their efficiency. However, linear attention tends to be l

3DTMDet: A Dual-Path Synergy Network of Transformer and SSM for 3D Object Detection in Point Clouds

arXiv:2605.15546v1 Announce Type: new Abstract: A fundamental challenge in point cloud object detection lies in the conflict between the extreme sparsity of distant points and the need for remote cont

A mental model for working with coding agents is that they're blind squirrels running into a maze and bumping into walls. You must place the…

researchfrancois-chollet--x

A mental model for working with coding agents is that they're blind squirrels running into a maze and bumping into walls. You must place the walls (verifiable constraints) strategically so that they e

A Model Can Help Itself: Reward-Free Self-Training for LLM Reasoning

arXiv:2510.18814v3 Announce Type: replace-cross Abstract: Can language models improve their reasoning performance without external rewards, using only their own sampled responses for training? We show

A Multi-Layer Cloud-IDS Pipeline with LLM and Adaptive Q-Learning Calibration

arXiv:2605.15889v1 Announce Type: cross Abstract: Security in cloud computing has become a major concern due to several factors such as layered cloud architectures, dynamic environments, and exposure

A numerical study into neural network surrogate model performance for uncertainty propagation

arXiv:2605.16078v1 Announce Type: cross Abstract: Neural network surrogate models have emerged as a promising approach to model solution fields for a wide variety of boundary value problems encountere

A Retrieval-Enhanced Transformer for Multi-Step Port-of-Call Sequence Prediction in Global Liner Shipping

arXiv:2605.15937v1 Announce Type: new Abstract: Accurate multi-step port-of-call sequence prediction is vital for tactical resource orchestration and logistical efficiency. However, existing methods s

A Statistical Analysis for Per-Instance Evaluation of Stochastic Optimizers: Avoiding Unreliable Conclusions

arXiv:2503.16589v2 Announce Type: replace Abstract: A key trait of stochastic optimizers is that multiple runs of the same optimizer in attempting to solve the same problem can produce different resul

A Topology-Aware Spatiotemporal Handover Framework for Continuous Multi-UAV Tracking

arXiv:2605.15779v1 Announce Type: cross Abstract: The integration of Unmanned Aerial Vehicles(UAVs) into Intelligent Transportation Systems (ITS) offers synoptic visibility for traffic monitoring, yet

A Unified Generative-AI Framework for Smart Energy Infrastructure: Intelligent Gas Distribution, Utility Billing, Carbon Analytics, and Quantum-Inspired Optimisation

arXiv:2605.16232v1 Announce Type: cross Abstract: The accelerating convergence of smart metering, generative artificial intelligence, and quantum-inspired combinatorial optimisation is reshaping how e

A Unified Perturbation Framework for Analyzing Leaderboard Stability and Manipulation

arXiv:2605.15761v1 Announce Type: new Abstract: Evaluation leaderboards such as LMArena play a central role in benchmarking large language models by aggregating pairwise human preferences into model r

AdaEraser: Training-Free Object Removal via Adaptive Attention Suppression

arXiv:2605.15921v1 Announce Type: new Abstract: Object removal aims to eliminate specified objects from images while plausibly inpainting the affected regions with background content. Current training

ADAPT: A Self-Calibrating Proactive Autoscaler for Container Orchestration

arXiv:2605.15788v1 Announce Type: cross Abstract: Proactive autoscaling for containerized workloads depends on knowing the provisioning delay, i.e., the time between a scaling decision and the moment

Adaptive Conformal Prediction for Quantum Machine Learning

arXiv:2511.18225v2 Announce Type: replace Abstract: Quantum machine learning seeks to leverage quantum computers to improve upon classical machine learning algorithms. Currently, robust uncertainty qu

'AI is hiking your energy bill' is the most popular political talking point of 2026. The data doesn't support it. A thread:

This thread examines the 2026 political claim that AI is significantly increasing energy bills, arguing that available data does not support this assertion as a major economic impact. The post likely

researchyann-lecun--x

Amortized Energy-Based Bayesian Inference

arXiv:2605.15407v1 Announce Type: cross Abstract: We consider amortized Bayesian inference for nonlinear inverse problems in settings where only samples from the joint distribution of parameters and o

An LLM-RAG Approach for Healthy Eating Index-Informed Personalized Food Recommendations

arXiv:2605.15213v1 Announce Type: cross Abstract: Diet quality is a leading determinant of chronic disease risk. Advances in artificial intelligence (AI) have enabled food recommendation systems to ad

Antidistillation Fingerprinting

arXiv:2602.03812v2 Announce Type: replace-cross Abstract: Model distillation enables efficient emulation of frontier large language models (LLMs), creating a need for robust mechanisms to detect when

AOT-POT: Adaptive Operator Transformation for Large-Scale PDE Pre-training

arXiv:2605.15793v1 Announce Type: new Abstract: Pre-training neural operators on diverse partial differential equation (PDE) datasets has emerged as a promising direction for building general-purpose

Approximating Global Contact-Implicit MPC via Sampling and Local Complementarity

arXiv:2505.13350v2 Announce Type: replace Abstract: To achieve general-purpose dexterous manipulation, robots must rapidly devise and execute contact-rich behaviors. Existing model-based controllers a

researcharxiv-cs-ro

Are VLMs Seeing or Just Saying? Uncovering the Illusion of Visual Re-examination

arXiv:2605.15864v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) often produce self-reflective statements like 'let me check the figure again' during reasoning. Do such statements trigg

researcharxiv-cs-cl

ART: Articulated Reconstruction Transformer

arXiv:2512.14671v3 Announce Type: replace Abstract: We introduce ART, Articulated Reconstruction Transformer -- a category-agnostic, feed-forward model that reconstructs complete 3D articulated object

Artificial Aphasias in Lesioned Language Models

arXiv:2605.16222v1 Announce Type: new Abstract: Aphasias, selective language impairments which can arise from brain damage, reveal the functional organization of human language by providing causal lin

researcharxiv-cs-cl

Asking the Right Questions: Improving Reasoning with Generated Stepping Stones

arXiv:2602.19069v2 Announce Type: replace Abstract: Recent years have witnessed tremendous progress in enabling LLMs to solve complex reasoning tasks such as math and coding. As we start to apply LLMs

Attention Dispersion in Dynamic Graph Transformers: Diagnosis and a Transferable Fix

arXiv:2605.16112v1 Announce Type: cross Abstract: Transformer-based architectures have become the dominant paradigm for Continuous-Time Dynamic Graph (CTDG) learning, yet their performance remains lim

Autoguided Online Data Curation for Diffusion Model Training

arXiv:2509.15267v2 Announce Type: replace-cross Abstract: The costs of generative model compute rekindled promises and hopes for efficient data curation. In this work, we investigate whether recently

BARRIER: Bounded Activation Regions for Robust Information Erasure

arXiv:2605.15737v1 Announce Type: new Abstract: Machine unlearning has reached a critical bottleneck. As traditional weight-space interventions focus primarily on erasing targeted concepts, they often