Search: “papers”

Learning features from Newton's algorithm: a way to accelerate nonlinear parametrized PDE solvers

model-releasesarxiv-cs-lg

arXiv:2607.28036v1 Announce Type: new Abstract: It is well known that Newton's method converges faster when the initial guess is closer to a root of a system of nonlinear equations. In this paper, a t

31 Jul 2026

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Optimizing Regret

DGX agent

arXiv:2607.18866v2 Announce Type: replace-cross Abstract: Building on the identity that expected regret equals the covariance between costs and decisions, this paper develops a derivative theory of th

safetyarxiv-cs-lg

31 Jul 2026

Physical prior guided cooperative learning framework for joint turbulence degradation estimation and infrared video restoration

arXiv:2408.04227v2 Announce Type: replace-cross Abstract: Infrared imaging and turbulence strength measurements are in widespread demand in many fields. This paper introduces a Physical Prior Guided C

researcharxiv-cs-cv

31 Jul 2026

Reviewer Scores Are Not Comparable Across Research Areas in ML Peer Review

arXiv:2607.27209v1 Announce Type: cross Abstract: Peer review at ML conferences increasingly relies on reviewer scores as the primary decision instrument. As submissions have scaled from thousands to

safetyarxiv-cs-lg

31 Jul 2026

Calibri: Enhancing Diffusion Transformers via Parameter-Efficient Calibration

model-releasesarxiv-cs-cv

arXiv:2603.24800v2 Announce Type: replace Abstract: In this paper, we uncover the hidden potential of Diffusion Transformers (DiTs) to significantly enhance generative tasks. Through an in-depth analy

Controlled Experiments on Lane Changing by Transitional Autonomous Vehicle: Dataset and Behavioral Insights

arXiv:2607.27085v1 Announce Type: new Abstract: This paper presents the North Carolina Transitional Autonomous Vehicle Lane-Changing (NC-tALC) dataset and uses it to characterize mandatory lane-changi

safetyarxiv-cs-ro

Field Codes for Distributed Coupling Samplers and Certified Empirical Transport

arXiv:2607.27078v1 Announce Type: cross Abstract: In this paper, we formulate three communication tasks for empirical optimal transport: distributed coupling sampling, cost-evaluable coupling output,

Ontology-driven personalized information retrieval for XML documents

arXiv:2603.21139v2 Announce Type: replace-cross Abstract: This paper addresses the challenge of improving information retrieval from semi-structured eXtensible Markup Language (XML) documents. Traditi

Risk-Aware Motion Planning with Learned Trajectory Primitives and Probabilistic Safety Assessment

model-releasesarxiv-cs-ro

arXiv:2607.26802v1 Announce Type: new Abstract: This paper presents a radial basis function network (RBFN)-informed motion planning framework for safe and efficient urban autonomous driving. The propo

RVC-NMPC: Nonlinear Model Predictive Control with Reciprocal Velocity Constraints for Mutual Collision Avoidance in Agile UAV Flight

arXiv:2512.08574v2 Announce Type: replace Abstract: This paper presents an approach to mutual collision avoidance based on Nonlinear Model Predictive Control (NMPC) with time-dependent Reciprocal Velo

applicationsarxiv-cs-ro

A Human-in-the-Loop Corpus for LLM-Based Simplification of Scientific Summaries

arXiv:2607.25630v1 Announce Type: cross Abstract: Interdisciplinary research is accelerating, yet scientific papers remain difficult to understand outside their home fields. We study large language mo

A Support-Set Algorithm for Optimization Problems with Nonnegative and Orthogonal Constraints

arXiv:2511.03443v2 Announce Type: replace-cross Abstract: In this paper, we investigate optimization problems with nonnegative and orthogonal constraints, where any feasible matrix of size n imes p ex

applicationsarxiv-cs-lg

A Unified Algorithmic Framework for Hybrid Reinforcement Learning in Tabular MDPs with Shifted Transition Dynamics

arXiv:2607.25207v1 Announce Type: new Abstract: This paper investigates a hybrid reinforcement learning setting in tabular Markov Decision Processes (MDPs), where an agent aims to learn an optimal pol

safetyarxiv-cs-lg

Adversarial Deepfake Generation and an Investigation of Purification-Based Adversarial Detection

arXiv:2607.25842v1 Announce Type: new Abstract: This paper describes the participation of team 'Go To Germany' in the ImageCLEF 2026 Deepfake Detection and Generation Task. For the image generation ta

researcharxiv-cs-cv

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction

arXiv:2607.25751v1 Announce Type: new Abstract: In this paper, we propose the Rule-based Visiting Circulation (RVC) model in tackling the challenge in the IEEE Big Data Cup 2022: Trip Destination Pred

COCO-OLAC: A Benchmark for Occluded Panoptic Segmentation and Image Understanding

model-releasesarxiv-cs-cv

arXiv:2409.12760v3 Announce Type: replace Abstract: To help address the occlusion problem in panoptic segmentation and image understanding, this paper proposes a new large-scale dataset named COCO-OLA

Computational Extraction of Legal Causes via al-Sabr wa al-Taqsim: A Set-Theoretic Formalization for Closed Fiqh Chapters

arXiv:2607.25605v1 Announce Type: new Abstract: This paper presents a set-theoretic formalization of the classical usuli method of al-Sabr wa al-Taqsim (Examination and Division) for extracting legal

applicationsarxiv-cs-ai

ContractHIL-HLS: Contract-Aligned Multi-Agent Workflow with Hardware-in-the-Loop Feedback for HLS Design

arXiv:2607.25283v1 Announce Type: new Abstract: This paper presents ContractHIL-HLS, a contract-aligned multi-agent workflow for practical high-level synthesis (HLS) engineering. The workflow makes th

safetyarxiv-cs-ai

Device Invariance using Domain Adaptation on Acoustic Scene Classification

arXiv:2607.25887v1 Announce Type: cross Abstract: This paper explores the effectiveness of domain adaptation techniques when using convolutional neural network (CNN)-based and transformer-based featur

Tutorials

Diffusion Disambiguation Models for Partial Label Learning

arXiv:2507.00411v2 Announce Type: replace Abstract: Learning from ambiguous labels is a long-standing problem in practical machine learning applications. The purpose of partial label learning (PLL) is

tutorialsarxiv-cs-lg

DS@GT ARC at CheckThat! 2026: LLM-Based Trace Ranking and Grouped Reward Modeling for Multilingual Numerical Claim Verification

arXiv:2607.25069v1 Announce Type: cross Abstract: Automated verification of numerical claims is a challenging problem, as it requires both language understanding and quantitative reasoning. This paper

Tutorials

From Idea to Classroom in Days: Using 'Vibe Coding' to Create a Programming Process Visualizer from IDE Activity Logs

arXiv:2607.24757v1 Announce Type: cross Abstract: This paper reports on the rapid development and classroom deployment of a Thonny log visualizer built using AI-assisted ``vibe coding'' to make studen

tutorialsarxiv-cs-ai

How Affect Propagates among LLM Agents: Emergent Emotional Contagion in Crowd Simulation

arXiv:2607.25140v1 Announce Type: new Abstract: This paper studies the behavior of language models in a multi-agent crowd simulation, focusing on how affect propagates among agents that perceive and a

agentsarxiv-cs-ai

Local Ai

Mondrian: On-Device High-Performance Video Analytics with Compressive Packed Inference

arXiv:2403.07598v2 Announce Type: replace Abstract: In this paper, we present Mondrian, an edge system that enables high-performance object detection on high-resolution video streams. Many lightweight

local-aiarxiv-cs-cv

Multi-Objective Kinodynamic Motion Planning with Asymptotic Pareto Optimality

arXiv:2607.15508v2 Announce Type: replace Abstract: In this paper, we address the challenge of multi-objective motion planning for systems under kinodynamic constraints. We consider three problem clas

researcharxiv-cs-ro

Tutorials

Patterns of Learner-AI Interaction and Academic Performance in an Object-Oriented Programming Course

arXiv:2607.24755v1 Announce Type: cross Abstract: This full research paper examines how different forms of learner-AI interaction relate to learning outcomes in object-oriented programming (OOP) cours

tutorialsarxiv-cs-ai

Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks

arXiv:2607.25877v1 Announce Type: new Abstract: This paper investigates how multi-agent systems (MAS)-based on large language models (LLMs) can support actuarial risk modelling, with a particular focu

agentsarxiv-cs-ai

S2A2: Audio-Visual Imitation Learning for Manipulation Tasks Using Acoustic Spatial Information

arXiv:2607.26047v1 Announce Type: new Abstract: Acoustic information provides rich cues about object location, material properties, and changes caused by contact or motion. This paper introduces a new

safetyarxiv-cs-ro

Shared Voxel-Map-Based Cooperative Indoor UAV Guidance with a Multi-Agent Soft Actor-Critic Controller

arXiv:2607.25728v1 Announce Type: cross Abstract: This paper presents a cooperative indoor UAV guidance framework that combines a shared voxel-map world model with a multi-agent Soft Actor-Critic (MAS

safetyarxiv-cs-ai

SourceMinds at CheckThat! 2026: NLI-Grounded Citation Auditing in a Multi-Agent Pipeline for Full Fact-Checking Article Generation

arXiv:2607.24802v1 Announce Type: cross Abstract: This paper presents our system for Task 3 of the CLEF 2026 CheckThat! Lab, which focuses on generating full fact-checking articles from claims, veraci

agentsarxiv-cs-cl

SpectONet: A Physics-Guided Spectral Deep Operator Network for Euler-Bernoulli Beam Dynamics

arXiv:2607.25790v1 Announce Type: cross Abstract: This paper proposes a novel physics-guided spectral deep operator network, termed SpectONet, for solving Euler-Bernoulli beam (EBB) vibration problems

applicationsarxiv-cs-ai

WALoMA: A Multitask Wireless Foundation Model via Adaptive Low-Rank Masked Autoencoders

model-releasesarxiv-cs-lg

arXiv:2607.25763v1 Announce Type: cross Abstract: This paper proposes a multitask wireless foundation model via adaptive low-rank masked autoencoders (WALoMA), a unified multi-task foundation model fo

An Exact Counterexample to Carlson's Associated-Prime Depth Conjecture from a Group of Order 128

arXiv:2607.23732v1 Announce Type: cross Abstract: In Question~3.1 of his 1995 paper on depth and transfer, Carlson asked whether the depth of a finite-group cohomology ring is always realized by the d

An Explicit Counterexample to Stanley's Rankwise Lower-Bound Conjecture for Differential Posets

arXiv:2607.22988v1 Announce Type: cross Abstract: In Problem~6 of his 1988 paper on differential posets, Stanley asked for the least possible cardinality of a fixed rank of an r-differential poset and

BioSentinel at EXIST 2026: Soft-Label Optimization with XLM-RoBERTa for Sexism Intent Classification in Memes

arXiv:2607.24137v1 Announce Type: new Abstract: This paper describes the BioSentinel team's participation in EXIST 2026 Task 2.2: Source Intention in Memes, part of the CLEF 2026 evaluation campaign.

researcharxiv-cs-cl

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,

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

researcharxiv-cs-cv

Fairness Interventions in Classification: A Study on AI Explainability

model-releasesarxiv-cs-ai

arXiv:2407.14766v4 Announce Type: replace-cross Abstract: This paper presents a philosophical and experimental study of fairness interventions in AI classification, centered on the explainability and

GEMCo: A Validated, Ethically Releasable Proxy for Inaccessible Counselling Data

model-releasesarxiv-cs-cl

arXiv:2607.23621v1 Announce Type: new Abstract: This paper presents GEMCo, a releasable, human-written proxy for inaccessible counselling data: 86 complete German e-mail counselling conversations (728

Local Ai

Gleam: Adaptive Network-Efficient CUDA API Remoting for Cross-Device GPU Sharing over LANs

arXiv:2607.23115v1 Announce Type: cross Abstract: This paper aims to enable computation- and communication-efficient GPU sharing across devices within local area networks (LANs), facilitating ubiquito

local-aiarxiv-cs-lg

Gradient Networks for Universal Magnetic Modeling of Synchronous Machines

arXiv:2602.14947v2 Announce Type: replace-cross Abstract: This paper presents a physics-constrained neural network framework for dynamic modeling of saturable synchronous machines, including spatial h

IJCB-AFMFR 2026: Competition on Adapting Foundation Models for Face Recognition Using Synthetic Training Data

arXiv:2607.24422v1 Announce Type: new Abstract: This paper presents a summary of the Competition on Adapting Foundation Models for Face Recognition Using Synthetic Training Data (AFMFR), held at the 2

safetyarxiv-cs-cv

LLM-Based vs. Lexicon-Based Sentiment Signals for Tail-Risk Detection in Meme Stocks

arXiv:2607.24072v1 Announce Type: new Abstract: This paper presents an empirical comparison of lexicon-based and Large Language Model (LLM)-based sentiment analysis for extracting market-relevant sign

researcharxiv-cs-cl

Long-Tailed Medical Image Classification

arXiv:2607.23883v1 Announce Type: new Abstract: In this paper, we examine the difficulties of using standard techniques for medical image classification due to long-tailed distributions (wherein rarer

safetyarxiv-cs-cv

Loss-Aware Feature-Map Pruning in Convolutional Neural Networks Using Multi-Armed Bandits

arXiv:2607.22564v1 Announce Type: new Abstract: Convolutional neural networks often contain redundant feature maps that increase storage and inference cost. This paper presents a loss-aware feature-ma

MPR-CiteG: Enhancing RAG with Multi-Portfolio Retrieval and Citation-Grounded Generation

arXiv:2607.22706v1 Announce Type: new Abstract: This paper presents the MPR-CiteG framework, which achieved second place in the ScienceON AI Challenge by addressing two fundamental challenges in gener

Multi-Modal Scene Graph with Kolmogorov-Arnold Experts for Audio-Visual Question Answering

model-releasesarxiv-cs-ai

arXiv:2511.23304v2 Announce Type: replace Abstract: In this paper, we propose a novel Multi-Modal Scene Graph with Kolmogorov-Arnold Expert Network for Audio-Visual Question Answering (SHRIKE). The ta

Mwando: Leveraging AI to Preserve and Teach shiKomori

arXiv:2607.23481v1 Announce Type: new Abstract: This paper presents Mwando, a virtual educational assistant designed to support the teaching and preservation of shiKomori, the language of the Comoros

agentsarxiv-cs-cl