research

Discrepancy-Rounded Fair Bandits with Static and Time-Varying Exposure Floors

arXiv:2607.22935v1 Announce Type: new Abstract: Minimum-exposure constraints arise in recommendation, content curation, and regulated allocation when each provider, arm, or group must receive guarante

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Disentangling Multi-View Scanning in Mamba for Network Traffic Anomaly Detection

DGX agent

arXiv:2607.22829v1 Announce Type: new Abstract: Network Traffic Anomaly Detection (NTAD) is a critical task in cybersecurity, yet timely and accurate anomaly detection remains challenging. Mamba has e

researcharxiv-cs-ai

28 Jul 2026

Distributed Convolutional Rank Regression over Decentralized Networks

arXiv:2607.23639v1 Announce Type: cross Abstract: This paper studies convolution rank regression (CRR) over decentralized distributed learning networks. We propose a novel decentralized CRR framework,

Distributional Split Criteria for Random Forests: Extensions, Shrinkage, and the Robustness of Mean Splitting

arXiv:2607.23721v1 Announce Type: cross Abstract: Distributional random forests replace mean-based CART splitting with criteria that compare the full conditional response distribution in candidate chi

Do Visual Features Improve Other-Initiated Repair Detection? A Dyadic Multimodal Approach

arXiv:2607.23845v1 Announce Type: new Abstract: Other-initiated Self-repair, or in short Other-initiated Repair (OIR), is an essential mechanism in conversational interaction, whereby a recipient sign

Does Graph Compression Preserve Signal Propagation?

arXiv:2607.23338v1 Announce Type: new Abstract: Graph compression reduces the computational cost of graph learning, but its effect on signal propagation remains largely underexplored. Existing work ev

DomainPilot: Domain-Level Loss-Guided Two-Stage Data Mixture Optimization for Efficient Language Model Fine-Tuning

arXiv:2607.22769v1 Announce Type: cross Abstract: The training efficacy of large language models (LLMs) is fundamentally constrained by the quality and composition of training data. Existing dynamic d

DP-IVON-Gradsq: Differentially Private Squared-Gradient Improved Variational Online Newton

arXiv:2607.23649v1 Announce Type: new Abstract: Differential privacy provides formal privacy guarantees for training neural networks on sensitive data, while Bayesian deep learning offers a principled

DreamStyle3D: Efficient 3D Stylized Asset Generation via Dual-Attention Disentanglement

arXiv:2607.24721v1 Announce Type: new Abstract: With the growth of gaming, animation, and virtual reality industries, the demand for efficient generation of stylized 3D assets is rapidly increasing. H

DRP-FLR: Data-Driven Assessment of Demand Response Potential for Flexible Load Regulation in Smart Grids

arXiv:2607.22590v1 Announce Type: cross Abstract: The rapid growth of AI workloads and renewable energy resources exacerbates supply-demand imbalance in power systems, making traditional load regulati

DSCH-Loss: A Dynamic Semantic Channel Objective for Deep Semantic Hashing

arXiv:2607.24567v1 Announce Type: new Abstract: Semantic hashing methods for generating short binary hash codes that allow efficient approximate nearest neighbor search in high-dimensional data spaces

DSTFView: Multi-View Cloud-Edge Workload Forecasting with Dual-Input Spatio-Temporal-Frequency Modeling

arXiv:2607.22565v1 Announce Type: new Abstract: With the widespread deployment of edge-side AI inference, edge platforms are increasingly required to support latency-sensitive, highly concurrent, and

EEGForceFusion: Joint Tokenised-Continuous Representation Learning for Subject-Independent Grasp Force Decoding

arXiv:2607.24126v1 Announce Type: cross Abstract: Brain-machine interfaces provide a link between neural activity and external devices, enabling restoration of motor function and advancing human-machi

Effective Parameters, Real Behavior: Renormalization for Robotics -- From Infinite Electron Mass to Sim-to-Real Gap

arXiv:2607.24079v1 Announce Type: new Abstract: Bridging the sim-to-real gap is a central problem in robotics, and the prevailing approach is to build increasingly accurate simulators. Here, we propos

researcharxiv-cs-ro

Effective Receptive Field Ordering Matters for Infrared Small Target Detection

arXiv:2607.23994v1 Announce Type: new Abstract: In this work, we investigate a previously unexplored architectural dimension for infrared small target detection: the organization of effective receptiv

EmoTrace: An Emotion Trajectory-Centered Framework for Psychological Support Dialogue Generation

arXiv:2607.23648v1 Announce Type: new Abstract: Using large language models (LLMs) to assist psychological counseling is an important task in the field of natural language processing. The construction

Ensembling LLM-Induced Decision Trees for Explainable and Robust Error Detection

arXiv:2512.07246v2 Announce Type: replace Abstract: Error detection (ED), which aims to identify incorrect or inconsistent cell values in tabular data, is important for ensuring data quality. Recent s

ESRVS: Extreme Semi-Supervised Retinal Vessel Segmentation with a Single Annotated Image

arXiv:2607.24453v1 Announce Type: cross Abstract: Learning from minimal human supervision is a long-standing goal in medical image analysis, where dense expert annotations are costly. We study retinal

Evaluating and Mitigating the Misguidance Effect of Buggy Code in LLM-Generated Unit Tests

arXiv:2607.22883v1 Announce Type: cross Abstract: While Large Language Models (LLMs) show great promise for automating unit test generation, recent studies suggest that the quality of generated tests

Evaluating the Impact of Reviewer Guideline Design on LLM-Based Automated Peer Review

arXiv:2607.22553v1 Announce Type: cross Abstract: Peer review is an essential process in scientific research, yet the growing workload has made its automation increasingly necessary. In this study, we

Event Driven Clustering Algorithm

arXiv:2602.00115v2 Announce Type: replace Abstract: This paper introduces a novel asynchronous, event-driven algorithm for real-time detection of small event clusters in event camera data. Similar to

EventOD: Event-Aware OD Flow Generation via LLM-Guided Semantic Modulation

arXiv:2607.22655v1 Announce Type: new Abstract: Estimating origin-destination (OD) flows under disruptive events is important for disaster response and urban resilience. Existing deep OD models traine

Every Client Is an Environment: Federated De-confounding for Spatio-Temporal Forecasting

arXiv:2607.24218v1 Announce Type: cross Abstract: Federated learning has emerged as a promising paradigm for spatio-temporal forecasting (STF), enabling collaborative model training without sharing ra

Evidence Attribution in Visual Document Understanding without Coordinates or Region Labels

arXiv:2607.24651v1 Announce Type: cross Abstract: Reliable visual document understanding requires a model to attribute each answer to the evidence regions that support it. Recent benchmarks and system

Exact and Asymptotically Complete Robust Verifications of Neural Networks via Ising Solvers

arXiv:2603.00408v2 Announce Type: replace-cross Abstract: We present an Ising-compatible framework for formal neural-network robustness verification under bounded input perturbations. For piecewise-li

Exact Evaluation of the Accuracy of Diffusion Models for Inverse Problems with Gaussian Data Distributions

arXiv:2507.07008v2 Announce Type: replace Abstract: Used as priors for Bayesian inverse problems, diffusion models have recently attracted considerable attention in the literature. Their flexibility a

Exact values and exact upper bounds for families of integers with arithmetic progression intersections (Erdos Problem #272)

arXiv:2607.23004v1 Announce Type: cross Abstract: Let t(N) be the largest t for which there exist distinct sets A_1,ots,A_t subseteq {1,ots,N} such that A_i ap A_j is a nonempty arithmetic progression

Explaining BiomedCLIP with Weighted Banzhaf Interactions Supported by Tree-Gram Parsing

arXiv:2607.23368v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are demonstrating significant capabilities in medical tasks like radiology analysis, yet providing faithful and interpre

Explaining GAND: A Resource on Gender-Ambiguous Natural Data & Contrastive Attribution

arXiv:2607.22546v1 Announce Type: new Abstract: Machine translation (MT) systems continue to produce gender-biased translations. In a time where self-expression is paramount, mistranslations based on

Exploration of the generative capabilities of Boltzmann machines applied to social systems under the majority rule

arXiv:2607.23349v1 Announce Type: new Abstract: We study the generative capabilities of Boltzmann machines to recover systems governed by the majority rule under critical conditions. To this end, we t

Extracting Algorithms in Pre-trained LLMs: A Case on Hidden Markov Models

arXiv:2607.22646v1 Announce Type: new Abstract: Large language models (LLMs) display a striking ability to predict next observations from Hidden Markov Models (HMMs) via in-context learning (ICL), but

Face Recognition with Machine Learning in OpenCV_ Fusion of the results with the Localization Data of an Acoustic Camera for Speaker Identification

arXiv:1707.00835v1 Announce Type: cross Abstract: This contribution gives an overview of face recogni-tion algorithms, their implementation and practical uses. First, a training set of different perso

Fashion-3DLR: A Controllable 3D Garment Generation Using Pairwise Fashion Elements for Intelligent Design

arXiv:2607.23189v1 Announce Type: cross Abstract: AI-generated content (AIGC) has made significant progress, with 2D generative models becoming ready-to-use tools for the digital fashion industry. How

Fast Fourier Convolutional GAN for 30 m Clear-Sky Land Surface Temperature Gap-Free Reconstruction

arXiv:2607.22734v1 Announce Type: new Abstract: Satellite-derived Land Surface Temperature (LST) provides spatially comprehensive data that ground stations cannot match. However, its utility is freque

FeelWorld: Visuo-Tactile World Model for Hierarchical Contact Prediction and Planning

arXiv:2607.24267v1 Announce Type: new Abstract: Humans plan physical interactions by imagining the possible outcomes of candidate actions. However, existing visual world models primarily capture appea

researcharxiv-cs-ro

Flick: Few Labels Text Classification using K-Aware Intermediate Learning in Multi-Task Low-Resource Languages

arXiv:2506.10292v2 Announce Type: replace-cross Abstract: Training deep learning networks with minimal supervision has gained significant research attention due to its potential to reduce reliance on

Flow4R: Unifying 4D Reconstruction and Tracking with Scene Flow

arXiv:2602.14021v2 Announce Type: replace Abstract: Reconstructing and tracking dynamic 3D scenes is a fundamental challenge in computer vision. Existing methods typically decouple geometry from motio

FMOPF: Latent Flow Matching with Constraint-Aware Interaction Priors for AC Optimal Power Flow

arXiv:2607.22788v1 Announce Type: cross Abstract: AC optimal power flow determines the minimum-cost generation dispatch under nonlinear power balance constraints and is solved thousands of times daily

Forgetting is Everywhere

arXiv:2511.04666v4 Announce Type: replace Abstract: A fundamental challenge in developing general learning algorithms is their tendency to forget past knowledge as they adapt to new data. Addressing t

Formalizing Flag Algebras in Lean

arXiv:2607.23500v1 Announce Type: cross Abstract: Razborov's flag algebra method is a powerful tool for proving asymptotic inequalities in extremal graph theory, often reducing the task to finding a f

Formally Verified Synthesizable Floating-Point Data Types in ARCH HDL

arXiv:2607.23715v1 Announce Type: new Abstract: We report the design and end-to-end verification of first-class IEEE-754 binary32 (FP32) and bfloat16 (BF16) arithmetic for ARCH, a hardware description

Foundation Models and Fine-Tuning: Toward a New Generation of Models for Time Series Forecasting

arXiv:2607.23146v1 Announce Type: new Abstract: Inspired by recent breakthroughs in large language models for natural language processing, foundation models have emerged as a promising paradigm for ze

Frequency-Aware Dual-Stream Learning for Balanced Realism and Fidelity in Electron Microscopy Imaging

arXiv:2607.22765v1 Announce Type: cross Abstract: Electron microscopy enables nanoscale cellular visualization but faces a trade-off between imaging resolution and acquisition speed. Existing learning

Frequency-Based Reservoir computing

arXiv:2607.24420v1 Announce Type: cross Abstract: Reservoir computing has emerged as an efficient machine learning framework for predicting time series generated by dynamical systems. In contrast to o

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis

arXiv:2607.24459v1 Announce Type: new Abstract: Large language models increasingly solve scientific-computing tasks, but executable feedback from one problem rarely becomes durable capability on subse

From peer review nuances to best practices

arXiv:2607.22681v1 Announce Type: cross Abstract: This report studies three nuances in peer review data: paper version, score version, and input format. We characterize how the variants differ, and me

From Physics to Surrogate Intelligence: A Unified Electro-Thermo-Optimization Framework for TSV Networks

arXiv:2603.29268v2 Announce Type: replace Abstract: High-density through-substrate vias (TSVs) enable 2.5D/3D heterogeneous integration but introduce significant signal-integrity and thermal-reliabili

From Score Learning to Discretized Sampling: An End-to-End Generalization Analysis of Diffusion Models

arXiv:2607.23226v1 Announce Type: new Abstract: Despite the empirical success of score-based diffusion models, a complete theoretical understanding of how finite-sample learning, network parameterizat