Search: “research”

A Robust widetilde{O}(1/sqrt{T}) Rate for Unprojected TD Learning with Linear Function Approximation

arXiv:2506.01052v3 Announce Type: replace Abstract: We investigate the finite-time convergence properties of Temporal Difference (TD) learning with linear function approximation, a cornerstone of rein

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A spectral audit framework reveals task-dependent aperiodic reliance across EEG and ECG deep learning

DGX agent

arXiv:2606.08583v1 Announce Type: new Abstract: Deep learning on physiological time series is interpreted through domain-specific features -- oscillatory rhythms in EEG, morphological complexes in ECG

researcharxiv-cs-lg

9 Jun 2026

A Theoretical Analysis of Memory and Overfitting Phenomena in Stochastic Interpolation Models

arXiv:2606.08554v1 Announce Type: new Abstract: This paper provides a theoretical account of memorization in stochastic interpolation models. By leveraging closed-form expressions for the optimal velo

A Unifying View of Attention Sinks: Two Algorithms, Two Solutions

arXiv:2606.08105v1 Announce Type: new Abstract: When attention concentrates on a single token, a sink, what is the model actually computing? Attention sinks are ubiquitous in softmax transformers, yet

A Variability-Based Framework for Interpretable Naming in Formal and Relational Concept Analysis

arXiv:2606.08477v1 Announce Type: new Abstract: Knowledge extraction from symbolic data often produces abstractions that are formally defined but not immediately interpretable by users. Formal Concept

AccioScene: Compositional 3D Scene Generation via Graph Diffusion and Interaction-driven Critics

arXiv:2502.06819v2 Announce Type: replace Abstract: This paper presents a framework for generating 3D indoor scenes from text prompts. Existing methods often formulate scene synthesis as an object lay

Advancements in Machine Learning and Deep Learning for Early Detection and Management of Mental Health Disorder

arXiv:2412.06147v2 Announce Type: replace Abstract: For the early identification, diagnosis, and treatment of mental health illnesses, the integration of deep learning (DL) and machine learning (ML) h

Adversarial Instance Generation and Robust Training for Neural Combinatorial Optimization with Multiple Objectives

arXiv:2601.01665v2 Announce Type: replace-cross Abstract: Deep reinforcement learning (DRL) has shown great promise in addressing multi-objective combinatorial optimization problems (MOCOPs). Neverthe

Airport Terminal Passenger Queue Forecasting for Departure Gates and Security Checkpoints

arXiv:2606.07622v1 Announce Type: new Abstract: Accurate passenger queue forecasting in airport terminals is essential for efficient departure operations, as it enables proactive congestion management

Algorithm for Contextual Queueing Bandits with Rate-Optimal Queue Length Regret

arXiv:2606.09668v1 Announce Type: new Abstract: Contextual queueing bandits provide a framework for learning to schedule heterogeneous jobs under unknown context-dependent service rates. Under stochas

All-in-One Augmented Reality Guided Head and Neck Tumor Resection

arXiv:2603.29495v2 Announce Type: replace Abstract: Positive margins are common in head and neck squamous cell carcinoma, yet intraoperative re-resection is often imprecise because margin locations ar

An Effective Router for Vision-Language Model Selection

arXiv:2606.08970v1 Announce Type: new Abstract: Vision-language models (VLMs) with varying performance and resource requirements are widely deployed, making it difficult for users to select the most a

An Enhanced Geometric-Spectral Feature Learning Framework for Airborne Multispectral Point Cloud Classification

arXiv:2606.09123v1 Announce Type: cross Abstract: Multispectral point cloud (MPC) is composed of 3D spatial-spectral information, which holds tremendous potential for accurate land-cover classificatio

An Interval Branch-and-Bound-Based Inverse Kinemetics Algorithm Towards Global Optimal Redundancy Resolution

arXiv:2104.12183v2 Announce Type: replace Abstract: The general inverse kinematics (IK) problem of a manipulator, namely that of acquiring the self-motion manifold (SMM) of all admissible joint angles

researcharxiv-cs-ro

An Opticalmechanics Framework for Dynamic Estimation of Multibody Systems

arXiv:2606.09383v1 Announce Type: new Abstract: Conventional dynamics analysis of the human body is often constrained by the need for contact force and torque sensors and controlled laboratory environ

Aperon Technical Report: Hierarchical No-Pointer Tangent-Local Search for High-Dimensional Approximate Nearest Neighbors

arXiv:2606.08813v1 Announce Type: cross Abstract: We present HNTL (Hierarchical No-pointer Tangent-Local), the core vector indexing and candidate generation framework of the Aperon vector memory syste

AQIFormer: A Transformer-Based Multi-View Architecture for Cross-City Air Quality Classification

arXiv:2606.07648v1 Announce Type: cross Abstract: Air pollution represents one of the most critical environmental and public health challenges globally, with traditional sensor-based monitoring system

Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape

arXiv:2403.06013v2 Announce Type: replace-cross Abstract: This paper delves into the critical area of deep learning robustness, challenging the conventional belief that classification robustness and e

Are Two Datasets Close Enough With Statistical Significance? A Kernel Distributional Closeness Testing Approach

arXiv:2507.12843v3 Announce Type: replace Abstract: Are two distributions close to each other with statistical significance? Distribution closeness testing (DCT) formalizes this question by testing wh

Model Releases

ArtiFact: A Large-Scale Multi-Modal Cultural Heritage Dataset

model-releasesarxiv-cs-ai

arXiv:2606.09648v1 Announce Type: cross Abstract: Multi-modal data management has emerged as a central research topic in the database community, spanning data integration, semantic query processing, a

Assessing Sample Quality in Conditional Generation under Compositional Shift

arXiv:2606.09601v1 Announce Type: new Abstract: Conditional generators provide a natural tool for controllable generation, including settings where the desired condition is a new composition of observ

Astro, I'm Home! Investigating Factors that Influence the Acceptance of Home Robots Using Supervised Machine Learning

arXiv:2606.07551v1 Announce Type: cross Abstract: The use of social robots in home environments is on the rise. This exploratory study applies regularization techniques (e.g., Lasso and Ridge regressi

researcharxiv-cs-ro

Asymptotic Optimality of Thompson Sampling for Risk-Averse Bandits with Sub-Gaussian Rewards

arXiv:2606.09191v1 Announce Type: new Abstract: We prove that rhoext{-}NPTS_{SG}, an anchor-free nonparametric Thompson Sampling algorithm for risk-averse bandits, achieves regret matching the instanc

ATM: Action-Consistency Transfer Matrix for Diagnosing and Improving Latent World Models

arXiv:2606.09028v1 Announce Type: cross Abstract: Latent world models are increasingly used for control and goal-conditioned planning, yet assessing whether their learned representations are useful fo

Attention at the Theoretical Minimum: A Mathematics of Arrays Framework for Memory-Optimal Transformer Kernels

arXiv:2606.07713v1 Announce Type: cross Abstract: The attention mechanism is the dominant computational bottleneck in modern transformer-based AI. Its standard implementation incurs quadratic memory t

AttentionCap: Transformer Based Capacitance Matrix Learning Toward Full-Chip Extraction

arXiv:2606.08161v1 Announce Type: new Abstract: As capacitance extraction accuracy of rule-based pattern matching becomes difficult to sustain at advanced nodes, a growing trend emerges to develop dee

AUCp: Pseudo-AUC for Inference Model Selection with Unlabeled Validation Data in Abnormality Detection

arXiv:2606.08742v1 Announce Type: new Abstract: Abnormality detection is a crucial yet challenging task in medical image analysis. Distinguishing abnormalities from normal data by learning to reconstr

Audio-FLAN: An Instruction-Following Dataset for Unified Audio Understanding and Generation of Speech, Music, and Sound

arXiv:2502.16584v2 Announce Type: replace-cross Abstract: Recent advancements in audio tokenization have significantly enhanced the integration of audio capabilities into large language models (LLMs).

Automating the Expert Eye: A System-Agnostic Deep Learning Framework for Rare Event Discovery in Imbalanced Force Spectroscopy

arXiv:2606.09541v1 Announce Type: cross Abstract: Single-Molecule Force Spectroscopy (SMFS) provides unprecedented insights into biomolecular mechanics, yet the high-throughput generation of force-ext

Back to Point: Exploring Point-Language Models for Zero-Shot 3D Anomaly Detection

arXiv:2603.21511v2 Announce Type: replace Abstract: Zero-shot (ZS) 3D anomaly detection is crucial for reliable industrial inspection, as it enables detecting and localizing defects without requiring

Backward Coherence and Hidden-State Stability in Recurrent Neural Networks: A Quasi-Reverse-Martingale Theory

arXiv:2606.08934v1 Announce Type: new Abstract: Recurrent neural networks maintain a hidden state h_t, but its probabilistic meaning is often unclear. We study hidden-state stability through backward

Balancing Real and Synthetic Data for CNN-based Masonry Crack Detection

arXiv:2606.08033v1 Announce Type: new Abstract: Cracks are a critical indicator of building health, and early stage identification is fundamental to prevent harmful damages. Advances in deep learning

Barycentric Projections of Optimal Transport Plans on Riemannian Manifolds

arXiv:2606.07926v1 Announce Type: cross Abstract: Optimal transport couplings are probabilistic objects, while many learning pipelines require deterministic maps. In Euclidean space, barycentric proje

BCG-FM: A Foundation Model for Ambient Cardiac Health Sensing

arXiv:2606.07692v1 Announce Type: cross Abstract: Foundation models for wearable biosignals have matched or exceeded supervised specialists across a range of clinical tasks, yet all rely on modalities

BEACON: Behavioral Entropy Aggregation for Cross-Model Hallucination Detection in Large Language Models

arXiv:2606.07528v1 Announce Type: cross Abstract: Hallucination in large language models (LLMs), defined as the generation of factually incorrect or unsupported content, remains a critical barrier to

Beyond Additivity: Causal Discovery in Location-Scale Noise Models with Hidden Variables

arXiv:2606.08196v1 Announce Type: cross Abstract: We study causal discovery from observational data when some variables are hidden and the data-generating process follows a location-scale noise model

Beyond Fixed Rounds: Data-Free Early Stopping for Practical Federated Learning

arXiv:2601.22669v3 Announce Type: replace Abstract: Federated Learning (FL) facilitates decentralized collaborative learning without transmitting raw data. However, reliance on fixed global rounds or

Beyond FLOPs: Benchmarking Real Inference Acceleration of LLM Pruning under a GEMM-Centric Taxonomy

arXiv:2606.09080v1 Announce Type: new Abstract: Pruning has emerged as a dominant paradigm for accelerating large language model (LLM) inference, spanning a broad spectrum of methods that remove compu

Beyond Humans: Multispecies Animal Face Recognition Using Transfer Learning

arXiv:2606.09353v1 Announce Type: cross Abstract: Individual animal recognition can be useful in the search for lost or stolen pets, the tracking of individuals of endangered species, and the recognit

Beyond Raw Signals: Undecoded Generative Latents as Privileged Synthetic Data

arXiv:2606.08336v1 Announce Type: new Abstract: While multimodal integration significantly improves computer vision models, deploying them incurs prohibitive inference costs and requires scarce, perfe

Beyond Spherical Harmonics: Rethinking Appearance Models for Radiance Reconstruction

arXiv:2606.09794v1 Announce Type: new Abstract: View-dependent appearance modeling remains a challenging problem in novel-view synthesis and reconstruction. Accurately representing complex angular eff

Beyond the Thin-Layer Limit: Differentiable Volumetric Training for Visible-Range Diffractive Neural Networks

arXiv:2606.07896v1 Announce Type: cross Abstract: Diffractive deep neural networks (D2NNs) promise miniaturized, power-efficient, light-speed optical front-ends for machine vision, yet the most mature

Biological Reasoning-Informed Regression for Interpretable Regulatory DNA Activity Prediction

arXiv:2606.08147v1 Announce Type: cross Abstract: DNA cis-regulatory elements (CREs) such as enhancers control gene expression levels. Accurately predicting regulatory activity from DNA sequences is v

BlendServe: Optimizing Offline Inference for Auto-regressive Large Models with Resource-aware Batching

arXiv:2411.16102v2 Announce Type: replace Abstract: Offline batch inference, which leverages the flexibility of request batching to achieve higher throughput and lower costs, is becoming more popular

BLM-SGAN: Bidirectional Language Modeling for Semantic-Spatial Text-to-Image Generation

arXiv:2606.08847v1 Announce Type: cross Abstract: Despite the success of image generation from text descriptions, it still faces challenges that are difficult to overcome in domains such as natural la

Brain2Text Decoding Model Reveals the Neural Mechanisms of Visual Semantic Processing

arXiv:2503.22697v3 Announce Type: replace-cross Abstract: Decoding sensory experiences from neural activity to reconstruct human-perceived visual stimuli and semantic content remains a challenge in ne

Bulk-boundary decomposition of neural networks

arXiv:2511.02003v2 Announce Type: replace Abstract: We present the bulk--boundary decomposition as a new framework for understanding the training dynamics of deep neural networks. Starting from the st

CAAL: Contextual Bandits based Online Hand-Craft Active Learning Strategy Selection

arXiv:2606.07910v1 Announce Type: new Abstract: The challenge with active learning algorithms is the uncertainty of the statistical distribution of unlabeled data, making it difficult to choose the be