research

The elbow statistic: Multiscale clustering statistical significance

arXiv:2603.03235v2 Announce Type: replace-cross Abstract: Selecting the number of clusters remains a fundamental challenge in unsupervised learning. Existing approaches typically focus on identifying

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The (Marginal) Value of a Search Ad: An Online Causal Framework for Repeated Second-price Auctions

DGX agent

arXiv:2605.01756v1 Announce Type: cross Abstract: Existing auto-bidding algorithms in digital advertising often treat the value of an ad opportunity as the revenue obtained when an ad is shown and/or

researcharxiv-cs-lg

5 May 2026

The Measure of Deception: An Analysis of Data Forging in Machine Unlearning

arXiv:2509.05865v2 Announce Type: replace Abstract: Motivated by privacy regulations and the need to mitigate the effects of harmful data, machine unlearning seeks to modify trained models so that the

The Multi-View Paradigm Shift in MRI Radiomics: Predicting MGMT Methylation in Glioblastoma

arXiv:2512.22331v2 Announce Type: replace Abstract: Non-invasive inference of molecular tumor characteristics from medical imaging is a central goal of radiogenomics, particularly in glioblastoma (GBM

The Norm-Separation Delay Law of Grokking: A First-Principles Theory of Delayed Generalization

arXiv:2603.13331v2 Announce Type: replace-cross Abstract: Grokking -- the sudden generalisation that appears long after a model has perfectly memorised its training data -- has been widely observed bu

The Pre-Training Study of Expanded-SPLADE Models on Web Document Titles

arXiv:2605.01407v1 Announce Type: cross Abstract: Masked Language Modeling (MLM) pre-training is one of the primary ways to initialize Neural Information Retrieval (IR) models prior to retrieval fine-

Tibetan-TTS:Low-Resource Tibetan Speech Synthesis with Large Model Adaptation

arXiv:2605.02496v1 Announce Type: cross Abstract: Tibetan text-to-speech (TTS) has long been challenged by scarce speech resources, significant dialectal variation, and the complex mapping between wri

Token-Efficient Change Detection in LLM APIs

arXiv:2602.11083v2 Announce Type: replace Abstract: Remote change detection in LLMs is a difficult problem. Existing methods are either too expensive for deployment at scale, or require initial white-

Toward a foundational thermal model for residential buildings

arXiv:2605.01364v1 Announce Type: new Abstract: The building energy community lacks a foundational thermal model, i.e., a single pretrained model capable of generalizing across diverse buildings, clim

Toward Resilient 5G Networks: Comparative Analysis of Federated and Centralized Learning for RF Jamming Detection

arXiv:2605.01705v1 Announce Type: cross Abstract: Jamming attacks are proliferating and pose a significant threat to the security of 5G and beyond networks. These attacks target 5G radio frequency (RF

Towards Systematic Generalization for Power Grid Optimization Problems

arXiv:2605.02026v1 Announce Type: new Abstract: AC Optimal Power Flow (ACOPF) and Security-Constrained Unit Commitment (SCUC) are fundamental optimization problems in power system operations. ACOPF se

Transfer Learning for Tonal Noise Prediction in VRF Units Using Thermodynamic and Vibration Signals

arXiv:2605.00895v1 Announce Type: cross Abstract: The second-order harmonic (2f) component generated by twin-rotary compressor is a dominant low-frequency noise source of variable refrigerant flow (VR

Trees and Graphs with Non Log-concave Dominating Set Sequence via AI Tools

arXiv:2605.02193v1 Announce Type: cross Abstract: We give new examples of graphs and trees with dominating set sequences that are not log-concave. These examples were generated by PatternBoost, a tran

TRIM: A Self-Supervised Video Summarization Framework Maximizing Temporal Relative Information and Representativeness

arXiv:2506.20588v2 Announce Type: replace Abstract: The increasing ubiquity of video content and the corresponding demand for efficient access to meaningful information have elevated video summarizati

TT4D: A Pipeline and Dataset for Table Tennis 4D Reconstruction From Monocular Videos

arXiv:2605.01234v1 Announce Type: new Abstract: We present TT4D, a large-scale, high-fidelity table tennis dataset. It provides 140+ hours of reconstructed singles and doubles gameplay from monocular

Unbox Responsible GeoAI: Navigating Climate Extreme and Disaster Mapping

arXiv:2605.00315v1 Announce Type: cross Abstract: As climate extreme and disaster events become more frequent and intense, Geospatial Artificial Intelligence (GeoAI) has emerged as a transformative ap

researcharxiv-cs-ai

Unifying Deep Stochastic Processes for Image Enhancement

arXiv:2605.01568v1 Announce Type: new Abstract: Deep stochastic processes have recently become a central paradigm for image enhancement, with many methods explicitly conditioning the stochastic trajec

Universality in Deep Neural Networks: An approach via the Lindeberg exchange principle

arXiv:2605.02771v1 Announce Type: cross Abstract: We consider the infinite-width limit of a fully connected deep neural network with general weights, and we prove quantitative general bounds on the 2-

Unsupervised Learning of Robust Spectral Shape Matching

arXiv:2304.14419v2 Announce Type: replace Abstract: We propose a novel learning-based approach for robust 3D shape matching. Our method builds upon deep functional maps and can be trained in a fully u

Validation of an AI-based end-to-end model for prostate pathology using long-term archived routine samples

arXiv:2605.02614v1 Announce Type: new Abstract: Artificial intelligence (AI) is becoming a clinical tool for prostate pathology, but generalization across variations in sample preparation and preserva

Validation of Whole-Slide Foundation Models for Image Retrieval in TCGA Data

arXiv:2605.00902v1 Announce Type: new Abstract: Foundation models are reshaping computational histopathology, yet their value for whole-slide image retrieval relative to strong patch-based and supervi

Vanast: Virtual Try-On with Human Image Animation via Synthetic Triplet Supervision

arXiv:2604.04934v2 Announce Type: replace Abstract: We present Vanast, a unified framework that generates garment-transferred human animation videos directly from a single human image, garment images,

Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration

arXiv:2509.10652v3 Announce Type: replace-cross Abstract: Generative AI is reshaping product design practices through 'vibe coding,' where product team members express intent in natural language and A

researcharxiv-cs-ai

ViewSAM: Learning View-aware Cross-modal Semantics for Weakly Supervised Cross-view Referring Multi-Object Tracking

arXiv:2605.02638v1 Announce Type: new Abstract: Cross-view Referring Multi-Object Tracking (CRMOT) aims to track multiple objects specified by natural language across multiple camera views, with globa

Virtual Scanning for NSCLC Histology: Investigating the Discriminatory Power of Synthetic PET

arXiv:2605.02746v1 Announce Type: new Abstract: Accurate histological differentiation between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) is critical for personalized treatment in non-small

Visual Chart Representations for Cryptocurrency Regime Prediction: A Systematic Deep Learning Study

arXiv:2605.00875v1 Announce Type: new Abstract: Technical traders have long relied on visual analysis of candlestick charts to identify market patterns and predict price movements. While deep learning

VoxAfford: Multi-Scale Voxel-Token Fusion for Open-Vocabulary 3D Affordance Detection

arXiv:2605.01365v1 Announce Type: new Abstract: Open-vocabulary 3D affordance detection requires localizing interaction regions on point clouds given novel affordance descriptions. Recent methods exte

VRGaussianAvatar: Integrating 3D Gaussian Avatars into VR

arXiv:2602.01674v2 Announce Type: replace Abstract: We present VRGaussianAvatar, an integrated system that enables real-time full-body 3D Gaussian Splatting (3DGS) avatars in virtual reality using onl

Watch Your Step: Information Injection in Diffusion Models via Shadow Timestep Embedding

arXiv:2605.00935v1 Announce Type: cross Abstract: Diffusion models have become the foundation of modern generative systems, with most research focusing primarily on improving generation efficiency and

What Does a Meow Mean? In Search of Intuitively Understandable Communication by a Nonverbal Companion Robot

arXiv:2605.01251v1 Announce Type: cross Abstract: Older adults living alone have a number of challenges, and robots can help with some of them--by providing reminders, initiating activity, or offering

researcharxiv-cs-ro

When Less is Enough: Efficient Inference via Collaborative Reasoning

arXiv:2605.01111v1 Announce Type: cross Abstract: In this work, we introduce DUET (Dual-model Efficient Two-stage inference), a collaborative inference framework in which a capable model and a lightwe

When To Adapt? Adapting the Model or Data in Federated Medical Imaging

arXiv:2605.00892v1 Announce Type: new Abstract: Federated learning enables collaborative model training across medical institutions without sharing raw data, but its performance is often limited by do

Where Do Prompt Perturbations Break Generation? A Segment-Level View of Robustness in LoRA-Tuned Language Models

arXiv:2605.01605v1 Announce Type: new Abstract: Large language models are sensitive to minor prompt perturbations, yet existing robustness methods usually enforce consistency at the whole-sequence lev

2D-SuGaR: Surface-Aware Gaussian Splatting for Geometrically Accurate Mesh Reconstruction

arXiv:2605.00569v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful technique for generating photorealistic renderings of a scene in real-time. However, the volumetr

A Comparative Study of QSPR Methods on a Unique Multitask PAMPA dataset

arXiv:2605.00508v1 Announce Type: new Abstract: We present a unique, multitask dataset comprising 143 drug and drug candidate molecules, each evaluated on in vitro, parallel artificial-membrane permea

A Comparative Study of UMAP and Other Dimensionality Reduction Methods

arXiv:2603.02275v2 Announce Type: replace Abstract: Uniform Manifold Approximation and Projection (UMAP) is a widely used manifold learning technique for dimensionality reduction. This paper studies U

A decade of quantum on the cloud

IBM Research reflects on ten years of quantum computing development and deployment through cloud-based platforms, documenting the evolution from early experimental systems to more practical quantum pr

researchibm-research

A Novel Patch-Based TDA Approach for Computed Tomography Imaging

arXiv:2512.12108v5 Announce Type: replace Abstract: The development of machine learning models based on computed tomography (CT) imaging has been a major focus due to the promise that imaging holds fo

Adaptive Geodesic Conformal Prediction for Egocentric Camera Pose Estimation

arXiv:2605.00233v1 Announce Type: new Abstract: Egocentric pose estimation for Augmented Reality (AR) and assistive devices requires not just accurate predictions but guaranteed uncertainty regions. C

Adaptive Node Feature Selection For Graph Neural Networks

arXiv:2510.03096v2 Announce Type: replace Abstract: We propose an adaptive node feature selection approach for graph neural networks (GNNs) that identifies and removes unnecessary features during trai

Adaptive Norm-Based Regularization for Neural Networks

arXiv:2605.00171v1 Announce Type: cross Abstract: In this paper, we study norm-based regularization methods for neural networks. We compare existing penalization approaches and introduce two regulariz

Adaptive Querying with AI Persona Priors

arXiv:2605.00696v1 Announce Type: cross Abstract: We study adaptive querying for learning user-dependent quantities of interest, such as responses to held-out items and psychometric indicators, within

ADVICE: Answer-Dependent Verbalized Confidence Estimation

arXiv:2510.10913v3 Announce Type: replace Abstract: Recent progress in large language models (LLMs) has enabled them to communicate their confidence in natural language, improving transparency and rel

Affinity Is Not Enough: Recovering the Free Energy Principle in Mixture-of-Experts

arXiv:2605.00604v1 Announce Type: new Abstract: Sparse MoE routing fails at domain transitions, where the current token belongs to one distribution and the next to another. In a controlled experiment

AIDA-ReID: Adaptive Intermediate Domain Adaptation for Generalizable and Source-Free Person Re-Identification

arXiv:2605.00111v1 Announce Type: new Abstract: Person re-identification (Re-ID) aims to match images of the same individual across non-overlapping camera views and remains challenging due to domain s

Aitchison Embeddings for Learning Compositional Graph Representations

arXiv:2605.00716v1 Announce Type: new Abstract: Representation learning is central to graph machine learning, powering tasks such as link prediction and node classification. However, most graph embedd

Batch Normalization for Neural Networks on Complex Domains

arXiv:2605.00467v1 Announce Type: new Abstract: Riemannian neural networks have proven effective in solving a variety of machine learning tasks. The key to their success lies in the development of pri

Beyond Decodability: Reconstructing Language Model Representations with an Encoding Probe

arXiv:2605.00607v1 Announce Type: new Abstract: Probing is widely used to study which features can be decoded from language model representations. However, the common decoding probe approach has two l