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A Benchmark for Early-stage Parkinson's Disease Detection from Speech

arXiv:2605.14066v1 Announce Type: cross Abstract: Early-stage Parkinson's disease (EarlyPD) detection from speech is clinically meaningful yet underexplored, and published results are hard to compare

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Research

A Block Coordinate Descent Method for Nonsmooth Composite Optimization under Orthogonality Constraints

DGX agent

arXiv:2304.03641v4 Announce Type: replace-cross Abstract: Nonsmooth composite optimization with orthogonality constraints has a wide range of applications in statistical learning and data science. How

researcharxiv-cs-lg

15 May 2026

A Calculus-Based Framework for Determining Vocabulary Size in End-to-End ASR

model-releasesarxiv-cs-cl

arXiv:2605.14427v1 Announce Type: new Abstract: In hybrid automatic speech recognition (ASR) systems, the vocabulary size is unambiguous, typically determined by the number of phones, bi-phones, or tr

A cross-species neural foundation model for end-to-end speech decoding

arXiv:2511.21740v5 Announce Type: replace-cross Abstract: Speech brain-computer interfaces (BCIs) aim to restore communication for people with paralysis by translating neural activity into text. Most

A CUBS-Compatible Ultrasound Morphology and Uncertainty-Aware Baseline for Carotid Intima-Media Segmentation and Preliminary Risk Prediction

arXiv:2605.14949v1 Announce Type: new Abstract: Carotid atherosclerosis is a major contributor to ischemic stroke and transient ischemic attack. Conventional ultrasound assessment is commonly based on

researcharxiv-cs-cv

A Deterministic Agentic Workflow for HS Tariff Classification: Multi-Dimensional Rule Reasoning with Interpretable Decisions

arXiv:2605.14857v1 Announce Type: new Abstract: Harmonized System (HS) tariff classification is a high-stakes, expert-level task in which a free-form product description must be mapped to a specific s

A Formative Study of Brief Affective Text as a Complement to Wearable Sensing for Longitudinal Student Health Monitoring

arXiv:2605.14360v1 Announce Type: cross Abstract: Wearable devices capture physiological and behavioral data with increasing fidelity, but the psychological context shaping these outcomes is difficult

researcharxiv-cs-cl

A Hardware-Aware, Per-Layer Methodology for Post-Training Quantization of Large Language Models

arXiv:2605.14929v1 Announce Type: new Abstract: Scaled Outer Product (SOP) is a post-training quantization methodology for large language model weights, designed to deliver near-lossless fidelity at 4

A Heterogeneous Temporal Memory Governance Framework for Long-Term LLM Persona Consistency

arXiv:2605.14802v1 Announce Type: new Abstract: Large language models often suffer from fact loss, timeline confusion, persona drift, and reduced stability during long-range interaction, especially un

researcharxiv-cs-ai

A Hormone-inspired Emotion Layer for Transformer language models (HELT)

arXiv:2605.13858v1 Announce Type: cross Abstract: Large Language Models have demonstrated remarkable capabilities in generating contextually relevant and grammatically correct text. However, they fund

researcharxiv-cs-cl

A Large Language Model Based Pipeline for Review of Systems Entity Recognition from Clinical Notes

model-releasesarxiv-cs-cl

arXiv:2506.11067v3 Announce Type: replace Abstract: Objective: Develop a cost-effective, large language model (LLM)-based pipeline for automatically extracting Review of Systems (ROS) entities from cl

A Minimal Agent for Automated Theorem Proving

arXiv:2602.24273v3 Announce Type: replace Abstract: We propose a minimal agentic baseline that enables systematic comparison across different AI-based theorem prover architectures. This design impleme

A Mutual Information Lower Bound for Multimodal Regression Active Learning

arXiv:2605.14917v1 Announce Type: new Abstract: Active learning for continuous regression has lacked an acquisition function that targets epistemic uncertainty when the predictive distribution is mult

Applications

A New Framework for Convex Clustering in Kernel Spaces: Finite Sample Bounds, Consistency and Performance Insights

arXiv:2511.05159v2 Announce Type: replace-cross Abstract: Convex clustering is a well-regarded clustering method, resembling the similar centroid-based approach of Lloyd's k-means, without requiring a

applicationsarxiv-cs-lg

A Non-Destructive Methodological Framework for Modernizing Legacy Clinical Reporting Systems for AI-Driven Pharmacoinformatics: A SAS Case Study

arXiv:2605.13905v1 Announce Type: cross Abstract: Drug development and pharmacovigilance are frequently bottlenecked by legacy clinical reporting pipelines. These monolithic systems encode regulatory-

A Non-Monotone Preconditioned Trust-Region Method for Neural Network Training

arXiv:2605.14860v1 Announce Type: cross Abstract: Training deep neural networks at scale can benefit from domain decomposition, where the network is split into subdomains trained in parallel and coupl

Applications

A Novel Schur-Decomposition-Based Weight Projection Method for Stable State-Space Neural-Network Architectures

arXiv:2605.14489v1 Announce Type: new Abstract: Building black-box models for dynamical systems from data is a challenging problem in machine learning, especially when asymptotic stability guarantees

applicationsarxiv-cs-lg

A Picture is Worth a Thousand Words? An Empirical Study of Aggregation Strategies for Visual Financial Document Retrieval

arXiv:2605.14581v1 Announce Type: cross Abstract: Visual RAG has offered an alternative to traditional RAG. It treats documents as images and uses vision encoders to obtain vision patch tokens. Howeve

A plug-and-play generative framework for multi-satellite precipitation estimation

arXiv:2605.14426v1 Announce Type: cross Abstract: Reliable precipitation monitoring is essential for disaster risk reduction, water resources management, and agricultural decision-making. Multi-source

researcharxiv-cs-ai

A Problem-Oriented Taxonomy of Evaluation Metrics for Time Series Anomaly Detection

arXiv:2511.18739v2 Announce Type: replace Abstract: Time series anomaly detection is widely used in IoT and cyber-physical systems, yet its evaluation remains challenging due to diverse application ob

Local Ai

A Prototyping Framework for Distributed Control of Multi-Robot Systems

arXiv:2605.15049v1 Announce Type: new Abstract: This paper presents a prototyping framework for distributed control of multi-robot systems, aimed at bridging theory and practical testing of distribute

local-aiarxiv-cs-ro

A Regret Perspective on Online Multiple Testing

arXiv:2605.13916v1 Announce Type: cross Abstract: Online Multiple Testing (OMT), a fundamental pillar of sequential statistical inference, traditionally evaluates the False Discovery Rate (FDR) and st

A Security Analysis of the OpenClaw AI Agent Framework

arXiv:2603.27517v3 Announce Type: replace-cross Abstract: AI agent frameworks connecting large language model (LLM) reasoning to host execution surfaces -- shell, filesystem, containers, and messaging

A Survey on Data-Dependent Worst-Case Generalization Bounds

model-releasesarxiv-cs-lg

arXiv:2605.13913v1 Announce Type: cross Abstract: Deep neural networks generalize well despite being heavily overparameterized, in apparent contradiction with classical learning theory based on unifor

A Systematic Evaluation of Imbalance Handling Methods in Biomedical Binary Classification

arXiv:2605.14147v1 Announce Type: new Abstract: Objective: The primary goal of this study was to systematically examine the impact of commonly used imbalance handling methods (IHMs) on predictive perf

A Tutorial on Cognitive Biases in Agentic AI-Driven 6G Autonomous Networks

arXiv:2510.19973v4 Announce Type: replace-cross Abstract: The path to higher network autonomy in 6G lies beyond the mere optimization of key performance indicators (KPIs), requiring systems that perce

Agents

A Two-Dimensional Framework for AI Agent Design Patterns: Cognitive Function and Execution Topology

arXiv:2605.13850v1 Announce Type: new Abstract: Existing frameworks for LLM-based agent architectures describe systems from a single perspective: industry guides (Anthropic, Google, LangChain) focus o

agentsarxiv-cs-ai

A Unified Geometric Framework for Weighted Contrastive Learning

arXiv:2605.13943v1 Announce Type: new Abstract: Contrastive learning (CL) aims to preserve relational structure between samples by learning representations that reflect a similarity graph. Yet, the ge

Tutorials

A Unified Knowledge Embedded Reinforcement Learning-based Framework for Generalized Capacitated Vehicle Routing Problems

arXiv:2605.14416v1 Announce Type: new Abstract: The Capacitated Vehicle Routing Problem (CVRP) is a fundamental NP-hard problem with broad applications in logistics and transportation. Real-world CVRP

tutorialsarxiv-cs-ai

Tutorials

AaSP: Aliasing-aware Self-Supervised Pre-Training for Audio Spectrogram Transformers

arXiv:2512.03637v2 Announce Type: replace-cross Abstract: Transformer-based audio self-supervised learning (SSL) models commonly use spectrograms, vision-style Transformers, and masked modeling object

tutorialsarxiv-cs-lg

Accelerated Sequential Flow Matching: A Bayesian Filtering Perspective

arXiv:2602.05319v3 Announce Type: replace Abstract: Sequential probabilistic inference from streaming observations requires modeling distributions over future trajectories as new observations arrive.

ACE-LoRA: Adaptive Orthogonal Decoupling for Continual Image Editing

model-releasesarxiv-cs-cv

arXiv:2605.14948v1 Announce Type: new Abstract: State-of-the-art diffusion models often rely on parameter-efficient fine-tuning to perform specialized image editing tasks. However, real-world applicat

Achieving Approximate Symmetry Is Exponentially Easier than Exact Symmetry

arXiv:2512.11855v2 Announce Type: replace-cross Abstract: Enforcing exact symmetry in machine learning models often yields significant gains in scientific applications, serving as a powerful inductive

Action-Conditioned Risk Gating for Safety-Critical Control under Partial Observability

arXiv:2605.14246v1 Announce Type: cross Abstract: Many safety-critical control problems are modeled as risk-sensitive partially observable Markov decision processes, where the controller must make dec

Action-Inspired Generative Models

arXiv:2605.14631v1 Announce Type: cross Abstract: We introduce Action-Inspired Generative Models (AGMs), a dual-network generative framework motivated by the observation that existing bridge-matching

Active Learners as Efficient PRP Rerankers

arXiv:2605.14236v1 Announce Type: cross Abstract: Pairwise Ranking Prompting (PRP) elicits pairwise preference judgments from an LLM, which are then aggregated into a ranking, usually via classical so

ActivePusher: Active Learning and Planning with Residual Physics for Nonprehensile Manipulation

arXiv:2506.04646v4 Announce Type: replace-cross Abstract: Planning with learned dynamics models offers a promising approach toward versatile real-world manipulation, particularly in nonprehensile sett

safetyarxiv-cs-lg

Addressing Terminal Constraints in Data-Driven Demand Response Scheduling

arXiv:2605.14741v1 Announce Type: cross Abstract: Electrified chemical processes are incentivized by exposure to time-varying electricity markets to operate flexibly, but participating in demand respo

Agents

Agentic AI Ecosystems in Higher Education: A Perspective on AI Agents to Emerging Inclusive, Agentic Multi-Agent AI Framework for Learning, Teaching and Institutional Intelligence

arXiv:2605.14266v1 Announce Type: new Abstract: Integration of artificial intelligent (AI) agents in higher education is transforming teaching, learning and administrative processes. Although existing

agentsarxiv-cs-ai

Agentic Design of Compositional Descriptors via Autoresearch for Materials Science Applications

arXiv:2605.14671v1 Announce Type: cross Abstract: Autoresearch offers a flexible paradigm for automating scientific tasks, in which an AI agent proposes, implements, evaluates, and refines candidate s

Agentic Recommender System with Hierarchical Belief-State Memory

arXiv:2605.14401v1 Announce Type: cross Abstract: Memory-augmented LLM agents have advanced personalized recommendation, yet existing approaches universally adopt flat memory representations that conf

Agentic Systems as Boosting Weak Reasoning Models

arXiv:2605.14163v1 Announce Type: new Abstract: Can a committee of weak reasoning-model calls reach the performance of much stronger models? We study verifier-backed committee search as inference-time

AgenticEval: Toward Agentic and Self-Evolving Safety Evaluation of Large Language Models

arXiv:2509.26100v2 Announce Type: replace Abstract: The rapid integration of Large Language Models (LLMs) into high-stakes domains necessitates reliable safety and compliance evaluation. However, exis

Agentifying Patient Dynamics within LLMs through Interacting with Clinical World Model

arXiv:2605.14723v1 Announce Type: new Abstract: Sepsis management in the ICU requires sequential treatment decisions under rapidly evolving patient physiology. Although large language models (LLMs) en

AgentTrap: Measuring Runtime Trust Failures in Third-Party Agent Skills

arXiv:2605.13940v1 Announce Type: cross Abstract: Third-party skills are becoming the package ecosystem for LLM agents. They package natural-language instructions, helper scripts, templates, documents

Agreement, Diversity, and Polarization Indices for Approval Elections

arXiv:2605.14983v1 Announce Type: cross Abstract: An index is a function that given an election outputs a value between 0 and 1, indicating the extent to which this election has a particular feature.

researcharxiv-cs-ai

AI-assisted cultural heritage dissemination: Comparing NMT and glossary-augmented LLM translation in rock art documents

arXiv:2605.14679v1 Announce Type: cross Abstract: Cultural heritage institutions increasingly disseminate research and interpretive materials globally, but multilingual dissemination is constrained by

Applications

AI-Driven Optimization under Uncertainty for Mineral Processing Operations

arXiv:2512.01977v2 Announce Type: replace-cross Abstract: The global capacity for mineral processing must expand rapidly to meet the demand for critical minerals, which are essential for building the

applicationsarxiv-cs-ai