Search: “research”

Towards Principled Test-Time Adaptation for Time Series Forecasting

arXiv:2605.17250v1 Announce Type: new Abstract: Test-time adaptation (TTA) has recently emerged as a promising approach for improving time series forecasting (TSF) under distribution shift. Existing T

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Towards Robust Argumentative Essay Understanding via TIDE: An Interactive Framework with Trial and Debate

DGX agent

arXiv:2605.17247v1 Announce Type: new Abstract: Argumentative essays serve as a vital medium for assessing critical thinking and reasoning skills, yet there is limited works on accurately understandin

researcharxiv-cs-ai

19 May 2026

Towards Ubiquitous Mapping and Localization for Dynamic Indoor Environments

arXiv:2605.18385v1 Announce Type: cross Abstract: We present UbiSLAM, an innovative solution for real-time mapping and localization in dynamic indoor environments. By deploying a network of fixed RGB-

Toy Combinatorial Interpretability Models Reveal Lottery Tickets in Early Feature Space

arXiv:2605.17704v1 Announce Type: new Abstract: The lottery ticket hypothesis posits that dense networks contain sparse subnetworks, ``winning tickets,'' that, when rewound to their initial weights an

TRACE: Trajectory Correction from Cross-layer Evidence for Hallucination Reduction

arXiv:2605.18163v1 Announce Type: new Abstract: Hallucination correction is not a one-direction problem. We show that intermediate layers are neither uniformly more truthful than final layers nor unif

Training Infinitely Deep and Wide Transformers

arXiv:2605.17660v1 Announce Type: cross Abstract: Transformers have become the dominant architecture in modern machine learning, yet the theoretical understanding of their training dynamics remains li

Trump’s “Great” Economy: -7% mortgage rates -6% inflation -$5 gas -More unemployed than job openings for 1st time since pandemic -Lowest Con…

Trump’s “Great” Economy: -7% mortgage rates -6% inflation -$5 gas -More unemployed than job openings for 1st time since pandemic -Lowest Consumer Sentiment in 74 years -CC Delinquencies highest since

researchyann-lecun--x

Two-Valued Symmetric Circulant Matrices: Applications in Deep Learning

arXiv:2605.16443v1 Announce Type: cross Abstract: Despite the success of deep neural networks in vision, medical diagnosis, and IoT scenarios, their deployment on resource-limited platforms poses seri

UB-SMoE: Universally Balanced Sparse Mixture-of-Experts for Resource-adaptive Federated Fine-tuning of Foundation Models

arXiv:2605.16690v1 Announce Type: new Abstract: Heterogeneous LoRA-rank methods address system heterogeneity in federated fine-tuning of foundation models by assigning client-specific ranks based on c

Applications

Uncertainty Quantification as a Principled Foundation for Explainable Artificial Intelligence: A Case Study of Counterfactual Explanations

arXiv:2502.17007v2 Announce Type: replace-cross Abstract: In this paper we argue that, to its detriment, transparency research overlooks many foundational concepts of artificial intelligence. As an il

applicationsarxiv-cs-ai

Understanding In-Context Learning on Structured Manifolds: Bridging Attention to Kernel Methods

arXiv:2506.10959v3 Announce Type: replace-cross Abstract: While in-context learning (ICL) has achieved remarkable success in natural language and vision domains, its theoretical understanding-particul

Universal Adversarial Triggers

arXiv:2605.17936v1 Announce Type: new Abstract: Recent works have illustrated that modern NLP models trained for diverse tasks ranging from sentiment analysis to language generation succumb to univers

researcharxiv-cs-cl

Universal Graph Backdoor Defense: A Feature-based Homophily Perspective

arXiv:2605.16815v1 Announce Type: cross Abstract: Graph neural networks (GNNs) have achieved remarkable success in relational learning. However, their vulnerability to graph backdoor attacks (GBAs) po

Universal Inverse Distillation for Matching Models with Real-Data Supervision (No GANs)

arXiv:2509.22459v4 Announce Type: replace-cross Abstract: While achieving exceptional generative quality, modern diffusion, flow, and other matching models suffer from slow inference, as they require

Unleashing Vision Transformer Potential In Image Quality Assessment via Global-Local Adaptive Interaction

arXiv:2605.17748v1 Announce Type: new Abstract: In the field of Blind Image Quality Assessment (BIQA), accurately predicting the perceptual quality of authentically distorted images remains highly cha

Unlocking the Potential of Diffusion Language Models through Template Infilling

arXiv:2510.13870v3 Announce Type: replace-cross Abstract: Diffusion Language Models (DLMs) have emerged as a promising alternative to Autoregressive Language Models, yet their inference strategies rem

UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models

arXiv:2605.17285v1 Announce Type: cross Abstract: Node representation learning, such as Graph Neural Networks (GNNs), has emerged as a pivotal method in machine learning. The demand for reliable expla

UST-Hand: An Uncertainty-aware Spatiotemporal Point Cloud Interaction Network for 3D Self-supervised Hand Pose Estimation

arXiv:2605.17742v1 Announce Type: new Abstract: Manually annotating accurate 3D hand poses is extremely time-consuming and labor-intensive. Existing self-supervised hand pose estimation methods levera

VA-Adapter: Adapting Ultrasound Foundation Model to Echocardiography Probe Guidance

arXiv:2510.06809v3 Announce Type: replace Abstract: Echocardiography is a critical tool for detecting heart diseases, yet its steep operational difficulty causes a shortage of skilled personnel. Probe

Variational Optimality of Follmer Processes in Generative Diffusions

arXiv:2602.10989v2 Announce Type: replace-cross Abstract: We construct and analyze generative diffusions that transport a point mass to a prescribed target distribution over a finite time horizon usin

Velocity and stroke rate reconstruction of canoe sprint team boats based on panned and zoomed video recordings

arXiv:2602.22941v2 Announce Type: replace Abstract: Pacing strategies, defined by velocity and stroke rate profiles, are essential for peak performance in canoe sprint. While GPS is the gold standard

VeriHGN: Heterogeneous Graph-Based Congestion Prediction for Chip Layout Verification

arXiv:2603.11075v2 Announce Type: replace-cross Abstract: As Very Large Scale Integration (VLSI) designs continue to scale in size and complexity, layout verification has become a central challenge in

VideoNeuMat: Neural Material Extraction from Generative Video Models

arXiv:2602.07272v2 Announce Type: replace Abstract: Creating photorealistic materials for 3D rendering requires exceptional artistic skill. Generative models for materials could help, but are currentl

Vidya: An AI-Driven Modular Pipeline for Archival Automation and Semantic Metadata Enrichment

arXiv:2605.16338v1 Announce Type: cross Abstract: The large-scale digitization of historical archives has created a paradox: 'dark data'-digital objects lacking metadata for retrieval. Manual archival

researcharxiv-cs-cl

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities

arXiv:2605.16880v1 Announce Type: new Abstract: Multimodal magnetic resonance imaging (MRI) is crucial for brain tumor segmentation, with many methods leveraging its four key modalities to capture com

Virtues of Ordered Chaos: Planning with Topple Actions in Tabletop Stack Rearrangement

arXiv:2605.17815v1 Announce Type: cross Abstract: Efficient object manipulation strategies have significant impact in automation applications. In this work, the stack rearrangement in tabletop setting

Vision Foundation Models as Generalist Tokenizers for Image Generation

arXiv:2605.18390v1 Announce Type: new Abstract: In this work, we explore the largely unexplored direction of building a generalist image tokenizer directly on top of a frozen vision foundation model (

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

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

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

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