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Unsupervised clustering and classification of upper limb EMG signals during functional movements: a data-driven

arXiv:2605.20599v1 Announce Type: new Abstract: This study presents a comprehensive approach for the clustering and classification of upper-limb surface electromyography (sEMG) signals during function

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UOTIP: Unbalanced Optimal Transport Map for Unpaired Inverse Problems

DGX agent

arXiv:2605.21094v1 Announce Type: new Abstract: We investigate unpaired image inverse problems, a challenging setting where only independent, non-paired sets of noisy measurements and clean target sig

researcharxiv-cs-lg

21 May 2026

USV: Towards Understanding the User-generated Short-form Videos

arXiv:2605.20838v1 Announce Type: new Abstract: Several large-scale video datasets have been published these years and have advanced the area of video understanding. However, the newly emerged user-ge

Variance Reduction for Expectations with Diffusion Teachers

arXiv:2605.21489v1 Announce Type: cross Abstract: Pretrained diffusion models serve as frozen teachers feeding downstream pipelines such as text-to-3D, single-step distillation, and data attribution.

Vega: Zero-knowledge proofs for digital identity in the age of AI

researchmicrosoft-research

Vega turns a full credential into a single proof, sharing only what is needed and nothing more, with performance that works in real apps. The post Vega: Zero-knowledge proofs for digital identity in t

VIHD: Visual Intervention-based Hallucination Detection for Medical Visual Question Answering

arXiv:2605.20772v1 Announce Type: new Abstract: While medical Multimodal Large Language Models (MLLMs) have shown promise in assisting diagnosis, they still frequently generate hallucinated responses

Weasel: Out-of-Domain Generalization for Web Agents via Importance-Diversity Data Selection

arXiv:2605.20291v1 Announce Type: new Abstract: Large language models (LLMs) have enabled web agents that follow natural language goals through multi-step browser interactions. However, agents fine-tu

What we find most useful about this study is the decomposition. For byte-level pretraining, the ordering is throughput first and boundary si…

What we find most useful about this study is the decomposition. For byte-level pretraining, the ordering is throughput first and boundary signal second; the boundary benefit can be recovered without a

researchnous-research--x

When Does Adaptation Win? Scaling Laws for Meta-Learning in Quantum Control

arXiv:2601.18973v4 Announce Type: replace Abstract: Quantum hardware suffers from intrinsic device heterogeneity and environmental drift, forcing practitioners to choose between suboptimal non-adaptiv

When Reasoning Supervision Hurts: TTCW-Based Long-Form Literary Review Generation

arXiv:2605.20364v1 Announce Type: new Abstract: Automatic evaluation of long-form literary writing remains challenging, as generic LLM-as-Judge approaches may not fully capture creativity-related dime

researcharxiv-cs-cl

Whenever an AI tells me I'm absolutely right, my trust in it drops by a bit

researchfrancois-chollet--x

Francois Chollet observes that AI systems which always affirm user correctness without nuance or disagreement reduce his confidence in their reliability. This reflects a concern that uncritical agreem

You Are What You Say: Exploiting Linguistic Content for VoicePrivacy Attacks

arXiv:2506.09521v2 Announce Type: replace-cross Abstract: Speaker anonymization systems hide the identity of speakers while preserving other information such as linguistic content and emotions. To eva

researcharxiv-cs-cl

3D aperture-engineered diffractive neural networks for super-resolution electromagnetic wave computing

arXiv:2603.00995v2 Announce Type: replace-cross Abstract: The rapid progress in 6G communication and high-bandwidth radar has driven an unprecedented surge in the spatial density of signal sources, re

3DMambaComplete: Exploring Structured State Space Model for Point Cloud Completion

arXiv:2404.07106v2 Announce Type: replace Abstract: Point cloud completion aims to generate a complete and high-fidelity point cloud from an initially incomplete and low-quality input. A prevalent str

4 big upgrades to Hermes Agents speed today `hermes update` to get moving faster now

Nous Research announced four major performance upgrades to their Hermes Agents framework, aimed at improving speed and efficiency. The update, referred to as the `hermes update`, enables faster execut

researchnous-research--x

A Cloud-Based Tool for Meteorite Recovery Using Drones and Machine Learning

arXiv:2605.19179v1 Announce Type: cross Abstract: We present a cloud-based tool that uses drones and machine learning to help recover instrumentally observed meteorite falls. We showcase a collection

A Data-Driven Approach to Idiomaticity Based on Experts' Criteria in Theoretical Linguistics

arXiv:2605.19575v1 Announce Type: new Abstract: The article observes data analysis of 286 multi-word expressions (MWEs) based on 16 lexical, grammatical and other criteria described in theoretical boo

researcharxiv-cs-cl

A Derandomization Framework for Structure Discovery: Applications in Neural Networks and Beyond

arXiv:2510.19382v2 Announce Type: replace-cross Abstract: Understanding the dynamics of feature learning in neural networks (NNs) remains a significant challenge. The work of (Mousavi-Hosseini et al.,

A first-order method for nonconvex-nonconcave minimax problems under a local Kurdyka-Lojasiewicz condition

arXiv:2507.01932v2 Announce Type: replace-cross Abstract: We study a class of nonconvex-nonconcave minimax problems in which the inner maximization problem satisfies a local Kurdyka-Lojasiewicz (KL) c

A Framework for Evaluating Zero-Shot Image Generation in Concept-based Explainability

arXiv:2605.19855v1 Announce Type: cross Abstract: Concept-based Explainable Artificial Intelligence (XAI) interprets deep learning models using human-understandable visual features (e.g., textures or

A Grid-Based Framework for E-Scooter Demand Representation and Temporal Input Design for Deep Learning: Evidence from Austin, Texas

arXiv:2603.13609v2 Announce Type: replace Abstract: Despite progress in deep learning for shared micromobility demand prediction, the systematic design and statistical validation of temporal input str

A Measure-Theoretic Analysis of Reasoning: Structural Generalization and Approximation Limits

arXiv:2605.19944v1 Announce Type: cross Abstract: While empirical scaling laws for LLM reasoning are well-documented, the theoretical mechanisms governing out-of-distribution (OOD) generalization rema

A Nash Equilibrium Framework For Training-Free Multimodal Step Verification

arXiv:2605.20033v1 Announce Type: new Abstract: Multimodal large language models often generate reasoning chains containing subtle errors that lead to incorrect answers. Current verification approache

A Practical Framework of Key Performance Indicators for Multi-Robot Lunar and Planetary Field Tests

arXiv:2601.20529v3 Announce Type: replace Abstract: Robotic prospecting for critical resources on the Moon, such as ilmenite, rare earth elements, and water ice, requires robust exploration methods gi

researcharxiv-cs-ro

A Two-Phase Adaptive Balanced Penalty Method for Controllable Pareto Front Learning under Split Feasibility Conditions

arXiv:2605.19306v1 Announce Type: new Abstract: We address the open problem of training hypernetworks for Controllable Pareto Front Learning (CPFL) under split feasibility conditions with rigorous the

Accurate, Efficient, and Explainable Deep Learning Approaches for Environmental Science Problems

arXiv:2605.19366v1 Announce Type: new Abstract: Environmental science plays a pivotal role in safeguarding ecosystems, a domain driven by large-scale, heterogeneous data. In the big data era, artifici

Adaptive Multi-Scale Goodness Aggregation for Forward-Forward Learning

arXiv:2605.18804v1 Announce Type: cross Abstract: We propose Adaptive Multi-Scale Goodness Aggregation (AMSGA), a novel extension of the Forward-Forward (FF) algorithm designed to improve stability, r

Adaptive Residual-Update Steering for Low-Overhead Hallucination Mitigation in Large Vision Language Models

arXiv:2511.10292v2 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) typically process visual inputs as a prefix to the language decoder. As the model autoregressively genera

Adynamical systems view of training generativemodels and the memorization phenomenon

arXiv:2605.19483v1 Announce Type: new Abstract: Using recent works of one of the authors (VSB) on collapse in generative models and two time scale dynamics in stochastic gradient descent in high dimen

AffectAI-Capture: A Reproducible Multimodal Protocol for Small-Group Meeting Research

arXiv:2605.19794v1 Announce Type: cross Abstract: We present AffectAI-Capture, a protocol for collecting synchronized multimodal data in four-person meeting-like interactions, combining eye tracking,

AffectVerse: Emotional World Models for Multimodal Affective Computing

arXiv:2605.19950v1 Announce Type: new Abstract: Humans infer emotions by integrating observed multimodal cues with expectations about how affective states may unfold. Existing multimodal large languag

ALDEN: Boosting Private Data Extraction from Retrieval-Augmented Generation Systems via Active Learning and Distribution Estimation

arXiv:2605.18762v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) is widely used to augment large language models with external knowledge retrieval to improve reliability and gene

An Efficient Multilevel Preconditioned Nonlinear Conjugate Gradient Method for Incremental Potential Contact

arXiv:2604.19892v1 Announce Type: cross Abstract: Incremental Potential Contact (IPC) guarantees intersection-free simulation but suffers from high computational costs due to the expensive Hessian ass

An Objective Performance Evaluation of the LSTM Networks in Time Series Classification

arXiv:2605.19311v1 Announce Type: new Abstract: The rapid adoption of deep learning has increasingly led to data-driven models replacing classical model-based algorithms, even in domains governed by w

AnchorFlow: Editable SVG Reconstruction via Sparse Anchor Point Fields

arXiv:2605.19551v1 Announce Type: cross Abstract: Image-to-SVG reconstruction aims to produce vector graphics that are faithful to raster inputs and easy to edit. Existing methods face a structural tr

AR1-ZO: Topology-Aware Rank-1 Zeroth-Order Queries for High-Rank LoRA Fine-Tuning

arXiv:2605.19767v1 Announce Type: cross Abstract: Zeroth-order (ZO) optimization enables large-language-model fine-tuning without storing backpropagation activations, while LoRA supplies compact train

Are Rationales Necessary and Sufficient? Tuning LLMs for Explainable Misinformation Detection

arXiv:2605.19285v1 Announce Type: cross Abstract: The rapid spread of misinformation on social media platforms has become a formidable challenge. To mitigate its proliferation, Misinformation Detectio

Are Watermarked Images Editable? SafeMark for Watermark-Preserving Text-Guided Image Editing

arXiv:2605.19511v1 Announce Type: new Abstract: This paper investigates a fundamental yet underexplored question: can watermarked images remain editable without compromising watermark integrity? We pr

Artificial Intelligence, conceptual metaphors and conceptual engineering: Are AI-based framings of human behaviour and cognition successful?

arXiv:2504.07756v2 Announce Type: replace Abstract: Understanding human behaviour, neuroscience and psychology using concepts from the domain of AI is increasing in popularity. Given the massive integ

Artificial Phantasia: Emergent Mental Imagery in Large Language Models

arXiv:2509.23108v2 Announce Type: replace Abstract: Can visual imagery be driven solely by language? This idea goes against cognitive science's traditional view that visual mental imagery is only poss

As always, 'hermes update'

Nous Research announced an update to their Hermes model, likely detailing improvements, new features, or performance enhancements to their open-source language model. The post was shared on X (formerl

researchnous-research--x

Atoms of Thought: Universal EEG Representation Learning with Microstates

arXiv:2605.20182v1 Announce Type: cross Abstract: Learning universal representations from electroencephalogram (EEG) signals is a cutting-edge approach in the field of neuroinformatics and brain-compu

Auditing Privacy in Multi-Tenant RAG under Account Collusion

arXiv:2605.19847v1 Announce Type: cross Abstract: Multi-tenant retrieval-augmented generation (RAG) services advertise per-account differential privacy as the operative leakage boundary: each account'

Automated Grading of Handwritten Mathematics Using Vision-Capable LLMs

arXiv:2605.19043v1 Announce Type: cross Abstract: Automated grading systems have enabled scalable assessment for many response types, but handwritten mathematics remains a barrier due to the complexit

Awakening the Hydra: Stabilizing Multi-Concept Backdoor Injection in Text-to-Image Diffusion Models

arXiv:2605.19698v1 Announce Type: cross Abstract: Text-to-image diffusion models are increasingly developed through open-source reuse and repeated downstream fine-tuning, where reused checkpoints are

BalanceRAG: Joint Risk Calibration for Cascaded Retrieval-Augmented Generation

arXiv:2605.20084v1 Announce Type: cross Abstract: Large language models (LLMs) can enhance factuality via retrieval-augmented generation (RAG), but applying RAG to every query is unnecessary when the

Bayesian Joint Model of Multi-Sensor and Failure Event Data for Multi-Mode Failure Prediction

arXiv:2506.17036v2 Announce Type: replace-cross Abstract: Modern industrial systems are often subject to multiple failure modes, and their conditions are monitored by multiple sensors, generating mult

Bilateral Teleoperation with Compliant 6-DOF Pose-and-Force Sensing

arXiv:2605.19255v1 Announce Type: new Abstract: Existing bilateral teleoperation platforms still rely on costly rigid six-axis force/torque sensors, tightly coupled leader-follower hardware, and kiloh

researcharxiv-cs-ro