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On the Complexity of the Discussion-based Semantics in Abstraction Argumentation

arXiv:2604.11480v1 Announce Type: new Abstract: We show that deciding whether an argument a is stronger than an argument b with respect to the discussion-based semantics of Amgoud and Ben-Naim is deci

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On the Convergence of Gradient Descent on Learning Transformers with Residual Connections

DGX agent

arXiv:2506.05249v4 Announce Type: replace Abstract: Transformer models have emerged as fundamental tools across various scientific and engineering disciplines, owing to their outstanding performance i

researcharxiv-cs-lg

14 Apr 2026

On the Effectiveness of Textual Prompting with Lightweight Fine-Tuning for SAM3 Remote Sensing Segmentation

arXiv:2512.15564v2 Announce Type: replace Abstract: Remote sensing (RS) image segmentation is constrained by the limited availability of annotated data and a gap between overhead imagery and natural i

On the Robustness of Watermarking for Autoregressive Image Generation

arXiv:2604.11720v1 Announce Type: cross Abstract: The proliferation of autoregressive (AR) image generators demands reliable detection and attribution of their outputs to mitigate misinformation, and

One Scale at a Time: Scale-Autoregressive Modeling for Fluid Flow Distributions

arXiv:2604.11403v1 Announce Type: cross Abstract: Analyzing unsteady fluid flows often requires access to the full distribution of possible temporal states, yet conventional PDE solvers are computatio

applicationsarxiv-cs-ai

One-Step Score-Based Density Ratio Estimation

arXiv:2604.10672v1 Announce Type: cross Abstract: Density ratio estimation (DRE) is a useful tool for quantifying discrepancies between probability distributions, but existing approaches often involve

Online Covariance Estimation in Averaged SGD: Improved Batch-Mean Rates and Minimax Optimality via Trajectory Regression

model-releasesarxiv-cs-lg

arXiv:2604.10814v1 Announce Type: new Abstract: We study online covariance matrix estimation for Polyak--Ruppert averaged stochastic gradient descent (SGD). The online batch-means estimator of Zhu, Ch

Online Covariance Matrix Estimation in Sketched Newton Methods

model-releasesarxiv-cs-lg

arXiv:2502.07114v2 Announce Type: replace-cross Abstract: Given the ubiquity of streaming data, online algorithms have been widely used for parameter estimation, with second-order methods particularly

Online Learning-Enhanced High Order Adaptive Safety Control

arXiv:2511.19651v2 Announce Type: replace Abstract: Control barrier functions (CBFs) are an effective model-based tool to formally certify the safety of a system. With the growing complexity of modern

safetyarxiv-cs-ro

Online Reasoning Video Object Segmentation

model-releasesarxiv-cs-cv

arXiv:2604.11411v1 Announce Type: new Abstract: Reasoning video object segmentation predicts pixel-level masks in videos from natural-language queries that may involve implicit and temporally grounded

Ontological Trajectory Forecasting via Finite Semigroup Iteration and Lie Algebra Approximation in Geopolitical Knowledge Graphs

arXiv:2604.10087v1 Announce Type: new Abstract: We present EL-DRUIN, an ontological reasoning system for geopolitical intelligence analysis that combines formal ontology, finite semigroup algebra, and

OOM-RL: Out-of-Money Reinforcement Learning Market-Driven Alignment for LLM-Based Multi-Agent Systems

arXiv:2604.11477v1 Announce Type: new Abstract: The alignment of Multi-Agent Systems (MAS) for autonomous software engineering is constrained by evaluator epistemic uncertainty. Current paradigms, suc

safetyarxiv-cs-ai

OOWM: Structuring Embodied Reasoning and Planning via Object-Oriented Programmatic World Modeling

arXiv:2604.09580v1 Announce Type: new Abstract: Standard Chain-of-Thought (CoT) prompting empowers Large Language Models (LLMs) with reasoning capabilities, yet its reliance on linear natural language

Agents

OpeFlo: Automated UX Evaluation via Simulated Human Web Interaction with GUI Grounding

arXiv:2604.09581v1 Announce Type: new Abstract: Evaluating web usability typically requires time-consuming user studies and expert reviews, which often limits iteration speed during product developmen

agentsarxiv-cs-ai

Open Datasets in Learning Analytics: Trends, Challenges, and Best PRACTICE

arXiv:2602.17314v2 Announce Type: replace-cross Abstract: Open datasets play a crucial role in three research domains that intersect data science and education: learning analytics, educational data mi

applicationsarxiv-cs-lg

Optimal Kinodynamic Motion Planning Through Anytime Bidirectional Heuristic Search with Tight Termination Condition

arXiv:2604.11587v1 Announce Type: new Abstract: This paper introduces Bidirectional Tight Informed Trees (BTIT*), an asymptotically optimal kinodynamic sampling-based motion planning algorithm that in

researcharxiv-cs-ro

Optimal L2 Regularization in High-dimensional Continual Linear Regression

arXiv:2601.13844v2 Announce Type: replace Abstract: We study generalization in an overparameterized continual linear regression setting, where a model is trained with L2 (isotropic) regularization acr

Optimal Rates for Generalization of Gradient Descent for Deep ReLU Classification

arXiv:2510.02779v3 Announce Type: replace Abstract: Recent advances have significantly improved our understanding of the generalization performance of gradient descent (GD) methods in deep neural netw

Optimal Stability of KL Divergence under Gaussian Perturbations

arXiv:2604.11026v1 Announce Type: cross Abstract: We study the problem of characterizing the stability of Kullback-Leibler (KL) divergence under Gaussian perturbations beyond Gaussian families. Existi

Optimization-Guided Diffusion for Interactive Scene Generation

arXiv:2512.07661v3 Announce Type: replace Abstract: Realistic and diverse multi-agent driving scenes are crucial for evaluating autonomous vehicles, but safety-critical events which are essential for

Local Ai

Optimizing Large Language Models: Metrics, Energy Efficiency, and Case Study Insights

arXiv:2504.06307v2 Announce Type: replace-cross Abstract: The rapid adoption of large language models (LLMs) has led to significant energy consumption and carbon emissions, posing a critical challenge

local-aiarxiv-cs-ai

Orthogonal machine learning for conditional odds and risk ratios

arXiv:2604.10412v1 Announce Type: cross Abstract: Conditional effects are commonly used measures for understanding how treatment effects vary across different groups, and are often used to target trea

safetyarxiv-cs-lg

Orthogonal Quadratic Complements for Vision Transformer Feed-Forward Networks

arXiv:2604.09709v1 Announce Type: cross Abstract: Recent bilinear feed-forward replacements for vision transformers can substantially improve accuracy, but they often conflate two effects: stronger se

Hardware

PA-SFM: Tracker-free differentiable acoustic radiation for freehand 3D photoacoustic imaging

arXiv:2604.09643v1 Announce Type: new Abstract: Three-dimensional (3D) handheld photoacoustic tomography typically relies on bulky and expensive external positioning sensors to correct motion artifact

hardwarearxiv-cs-cv

PAC-BENCH: Evaluating Multi-Agent Collaboration under Privacy Constraints

arXiv:2604.11523v1 Announce Type: new Abstract: We are entering an era in which individuals and organizations increasingly deploy dedicated AI agents that interact and collaborate with other agents. H

PAC learning PDFA from data streams

arXiv:2604.02244v3 Announce Type: replace-cross Abstract: This is an extended version of our publication Learning state machines from data streams: A generic strategy and an improved heuristic, Intern

Pacing Opinion Polarization via Graph Reinforcement Learning

arXiv:2602.23390v2 Announce Type: replace-cross Abstract: Opinion polarization moderation has been studied mainly as an analytical optimization problem under the Friedkin Johnson FJ model, where inter

applicationsarxiv-cs-lg

PACO: Proxy-Task Alignment and Online Calibration for On-the-Fly Category Discovery

arXiv:2604.11484v1 Announce Type: new Abstract: On-the-Fly Category Discovery (OCD) requires a model, trained on an offline support set, to recognize known classes while discovering new ones from an o

Local Ai

Pair2Scene: Learning Local Object Relations for Procedural Scene Generation

arXiv:2604.11808v1 Announce Type: new Abstract: Generating high-fidelity 3D indoor scenes remains a significant challenge due to data scarcity and the complexity of modeling intricate spatial relation

local-aiarxiv-cs-cv

Pando: Do Interpretability Methods Work When Models Won't Explain Themselves?

arXiv:2604.11061v1 Announce Type: cross Abstract: Mechanistic interpretability is often motivated for alignment auditing, where a model's verbal explanations can be absent, incomplete, or misleading.

Panoptic Pairwise Distortion Graph

arXiv:2604.11004v1 Announce Type: cross Abstract: In this work, we introduce a new perspective on comparative image assessment by representing an image pair as a structured composition of its regions.

PanoSAMic: Panoramic Image Segmentation from SAM Feature Encoding and Dual View Fusion

arXiv:2601.07447v2 Announce Type: replace Abstract: Existing image foundation models are not optimized for spherical images having been trained primarily on perspective images. PanoSAMic integrates th

researcharxiv-cs-cv

PaperScope: A Multi-Modal Multi-Document Benchmark for Agentic Deep Research Across Massive Scientific Papers

arXiv:2604.11307v1 Announce Type: new Abstract: Leveraging Multi-modal Large Language Models (MLLMs) to accelerate frontier scientific research is promising, yet how to rigorously evaluate such system

Para-B&B: Load-Balanced Deterministic Parallelization of Solving MIP

arXiv:2604.09556v1 Announce Type: cross Abstract: Mixed-integer programming (MIP) extends linear programming by incorporating both continuous and integer decision variables, making it widely used in p

Parallelism and Generation Order in Masked Diffusion Language Models: Limits Today, Potential Tomorrow

arXiv:2601.15593v2 Announce Type: replace-cross Abstract: Masked Diffusion Language Models (MDLMs) promise parallel token generation and arbitrary-order decoding, yet it remains unclear to what extent

Parameter Efficient Fine-tuning for Domain-specific Gastrointestinal Disease Recognition

model-releasesarxiv-cs-cv

arXiv:2604.10451v1 Announce Type: new Abstract: Despite recent advancements in the field of medical image analysis with the use of pretrained foundation models, the issue of distribution shifts betwee

Particle Diffusion Matching: Random Walk Correspondence Search for the Alignment of Standard and Ultra-Widefield Fundus Images

arXiv:2604.10085v1 Announce Type: new Abstract: We propose a robust alignment technique for Standard Fundus Images (SFIs) and Ultra-Widefield Fundus Images (UWFIs), which are challenging to align due

PAS: Estimating the target accuracy before domain adaptation

arXiv:2604.09863v1 Announce Type: cross Abstract: The goal of domain adaptation is to make predictions for unlabeled samples from a target domain with the help of labeled samples from a different but

Tutorials

PASTA: Vision Transformer Patch Aggregation for Weakly Supervised Target and Anomaly Segmentation

arXiv:2604.09701v1 Announce Type: new Abstract: Detecting unseen anomalies in unstructured environments presents a critical challenge for industrial and agricultural applications such as material recy

tutorialsarxiv-cs-cv

PAT: Privacy-Preserving Adversarial Transfer for Accurate, Robust and Privacy-Preserving EEG Decoding

arXiv:2412.11390v3 Announce Type: replace-cross Abstract: An electroencephalogram (EEG)-based brain-computer interface (BCI) enables direct communication between the brain and external devices. Howeve

safetyarxiv-cs-lg

PatchRecall: Patch-Driven Retrieval for Automated Program Repair

arXiv:2604.10481v1 Announce Type: cross Abstract: Retrieving the correct set of files from a large codebase is a crucial step in Automated Program Repair (APR). High recall is necessary to ensure that

researcharxiv-cs-cl

Pay Less Attention to Function Words for Free Robustness of Vision-Language Models

arXiv:2512.07222v3 Announce Type: replace-cross Abstract: To address the trade-off between robustness and performance for robust VLM, we observe that function words could incur vulnerability of VLMs a

researcharxiv-cs-cl

PEMANT: Persona-Enriched Multi-Agent Negotiation for Travel

arXiv:2604.10475v1 Announce Type: new Abstract: Modeling household-level trip generation is fundamental to accurate demand forecasting, traffic flow estimation, and urban system planning. Existing stu

safetyarxiv-cs-ai

PepBenchmark: A Standardized Benchmark for Peptide Machine Learning

arXiv:2604.10531v1 Announce Type: cross Abstract: Peptide therapeutics are widely regarded as the 'third generation' of drugs, yet progress in peptide Machine Learning (ML) are hindered by the absence

Perceived Importance of Cognitive Skills Among Computing Students in the Era of AI

arXiv:2604.10730v1 Announce Type: cross Abstract: The availability and increasing integration of generative AI tools have transformed computing education. While AI in education presents opportunities,

applicationsarxiv-cs-ai

PERCEPT-Net: A Perceptual Loss Driven Framework for Reducing MRI Artifact Tissue Confusion

arXiv:2604.10439v1 Announce Type: new Abstract: Purpose: Existing deep learning-based MRI artifact correction models exhibit poor clinical generalization due to inherent artifact-tissue confusion, fai

researcharxiv-cs-cv

Agents

Perception-aware Exploration for Consumer-grade UAVs

arXiv:2511.14393v2 Announce Type: replace Abstract: In our work, we extend the current state-of-the-art approach for autonomous multi-UAV exploration to consumer-level UAVs, such as the DJI Mini 3 Pro

agentsarxiv-cs-ro

Perception Is All You Need: A Neuroscience Framework for Low Cost Sensorless Gaze in HRI

arXiv:2604.09829v1 Announce Type: new Abstract: Gaze-following in child-robot interaction improves attention, recall, and learning, but requires expensive platforms ($30,000+), sensors, algorithms, an

researcharxiv-cs-ro