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Monotonic anomaly detection

arXiv:2410.23158v3 Announce Type: replace Abstract: Semi-supervised anomaly detection is based on the principle that any record that looks different from normal training data is a potential anomaly. H

Morphology signal in whole slide image foundation models can automatically triage slides

Source

Human DGX agent

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Clear filters

arXiv:2609.01987v1 Announce Type: new Abstract: Patient exams in the cancer diagnosis and staging process typically generate several whole slide images (WSIs). One of the initial steps in training mod

model-releasesarxiv-cs-cv

3 Sept 2026

MS-MEM: Multi-Skill Manipulation-Enhanced Mapping via Uncertainty- and Disturbance-Aware Action Selection

arXiv:2609.02493v1 Announce Type: new Abstract: Accurate scene understanding in confined, cluttered spaces such as shelves is essential for service robots, as many everyday tasks require them to locat

researcharxiv-cs-ro

MUDIDI: A Two-Stage Framework for Multilingual Dictionary Digitization with Language Models

model-releasesarxiv-cs-cl

arXiv:2606.09435v2 Announce Type: replace Abstract: Multilingual dictionaries are among the most valuable documentary resources for low-resource and endangered languages, yet many remain available onl

Agents

Multi-Agent Retrieval-Augmented Generation for Efficient Cloud Knowledge Base Search in Telecom SNOC Environment

arXiv:2609.01618v1 Announce Type: cross Abstract: Telecom Service and Network Operations Centers (SNOCs) rely on large collections of cloud documents, including Standard Operating Procedures (SOPs), v

agentsarxiv-cs-lg

Multi-Tool Image Editing Attribution in Facial Forgery

arXiv:2609.02751v1 Announce Type: new Abstract: As generative AI tools become increasingly powerful and easy to use, people can easily edit portrait images with a prompt, necessitating the task of ima

researcharxiv-cs-cv

MultiGhostBench: A Multilingual Benchmark for Long-Form LLM-Generated Text Attribution under Distribution Shifts

arXiv:2609.02379v1 Announce Type: cross Abstract: While existing work on LLM authorship attribution (AA) has made progress, available benchmarks remain limited, often focusing on English, controlled s

Hardware

MultiGraspNet: A Multitask 3D Vision Model for Multi-gripper Robotic Grasping

arXiv:2602.06504v2 Announce Type: replace-cross Abstract: Vision-based models for robotic grasping automate critical, repetitive, and draining industrial tasks. Existing approaches are typically limit

hardwarearxiv-cs-cv

Multimodal Language Models as Text-to-Image Model Evaluators

arXiv:2505.00759v3 Announce Type: replace-cross Abstract: The steady improvements of text-to-image (T2I) generative models lead to slow deprecation of automatic evaluation benchmarks that rely on stat

Local Ai

MuyBridge: Mobile Human Center-of-Mass Estimation from Monocular Video via Sparse Fusion

arXiv:2609.02854v1 Announce Type: new Abstract: The 3D center of mass (CoM) is a primary quantity in the biomechanical analysis of sport, rehabilitation, and clinical movement, yet existing 3D pose tr

local-aiarxiv-cs-cv

MV-dVRK: A Multi-Viewpoint Benchmark for Spatial Surgical Perception

model-releasesarxiv-cs-cv

arXiv:2609.02717v1 Announce Type: new Abstract: Large-scale training and refined optimization techniques have greatly improved sparse multi-view 3D reconstruction. Despite their relevance to surgery,

NE-R1: Enhancing Named Entity Recognition Model via Reinforcement Learning

arXiv:2609.02366v1 Announce Type: cross Abstract: Named Entity Recognition (NER) has achieved substantial progress since the advent of large language models (LLMs). Nevertheless, the recognition of lo

NeoMME: A Single-Tower Multimodal-Native Multilingual Foundation Encoder for Efficient Fine-Tuning and Inference

arXiv:2609.01657v1 Announce Type: cross Abstract: Multimodal models often build on architectures designed for generative vision-language modeling, typically combining separately pretrained vision enco

Applications

Network-Aware Forecasting on Wireless Access Points

arXiv:2609.01957v1 Announce Type: cross Abstract: Enterprise wireless access points (APs) are promising platforms for predictive machine learning (ML), but their primary responsibility remains providi

applicationsarxiv-cs-lg

Neural operators approximate strongly continuous convex monotone semigroups

arXiv:2609.02727v1 Announce Type: cross Abstract: We approximate strongly continuous convex monotone semigroups by learning their Chernoff-type one-step operators with neural operators. First, we intr

Neural Variational Cut Posteriors without Upstream Data

model-releasesarxiv-cs-lg

arXiv:2510.10268v3 Announce Type: replace-cross Abstract: In many applications, one must propagate parameter uncertainty from an earlier (upstream) analysis, available as samples, to subsequent (downs

No Data Wasted: A Semi-supervised Generative Model for Incomplete Multi-view Data Integration with Missing Labels

arXiv:2508.11180v2 Announce Type: replace-cross Abstract: Multi-view learning is widely applied to real-life datasets, but it often suffers from both missing views and missing labels. Prior probabilis

tutorialsarxiv-cs-ai

Nonasymptotic CLT and Error Bounds for Linear Two-Time-Scale Stochastic Approximation

arXiv:2502.09884v4 Announce Type: replace-cross Abstract: We consider linear two-time-scale stochastic approximation algorithms driven by martingale noise. Recent applications in machine learning moti

Not All Agreement Counts as Corroboration: Provenance-Conserving Multi-View Fusion for Typed Action Admission in Human-Robot Collaboration

arXiv:2609.01662v1 Announce Type: cross Abstract: For embodied systems, predictive agreement alone does not determine whether evidence warrants action; evidential origin matters. Repeated inference ov

Agents

NS-Copilot: An LLM-Driven Agent System for Autonomous Neuroscience Analysis

arXiv:2609.01971v1 Announce Type: new Abstract: AI is rapidly advancing neuroscience, yet many laboratories fail to fully unleash its potential due to significant interdisciplinary barriers. While pre

agentsarxiv-cs-cl

NS-VLA: Towards Neuro-Symbolic Vision-Language-Action Models

arXiv:2603.09542v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models are formulated to ground instructions in visual context and generate action sequences for robotic manipulation.

safetyarxiv-cs-ro

OBJECTION! Lawyer Agents Mitigate Guilty Bias in Legal Judgment Prediction

arXiv:2609.02158v1 Announce Type: cross Abstract: Legal Judgment Prediction (LJP) models are typically trained on documents that describe facts from a prosecutorial perspective. Existing datasets furt

safetyarxiv-cs-ai

oHC: Orthogonal Hyper-Connections on SO(4) via Quaternions

arXiv:2609.02672v1 Announce Type: new Abstract: Hyper-Connections (HC) replace the single residual stream of a Transformer with n parallel ones, mixing them at every layer with a learned n imes n resi

researcharxiv-cs-cl

Omega-N: Interpretable Structural Node Descriptors and Their Applicability Domain

arXiv:2609.01633v1 Announce Type: cross Abstract: A composite structural index summarises a network in one number; for a triangle-based index it is spectrally redundant: Tr(A^3) is the third moment of

safetyarxiv-cs-lg

Agents

OmegaUse-SOP: SOP Engineering for Professional Computer Use from Human Demonstrations

arXiv:2609.02149v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly evolving from conversational assistants into agents capable of operating external digital environments.

agentsarxiv-cs-ai

On Cost-Aware Designs for Sequential Hypothesis Testing

arXiv:2512.19067v2 Announce Type: replace-cross Abstract: We introduce Cost-Aware (CA) Sequential Hypothesis Testing (CASHT), in which an active decision-maker selects sensing actions with differing,

safetyarxiv-cs-lg

On-Policy Distillation Meets Off-Policy GRPO: Training Compact Instruction-Following Rerankers

arXiv:2609.01947v1 Announce Type: cross Abstract: Compact instruction-following rerankers are attractive for deployment, but conventional distillation pipelines typically train students by offline imi

One Demonstration, Many Objects: Generalizing Manipulation via Local Contact Geometry

arXiv:2609.01938v1 Announce Type: new Abstract: Dexterous manipulation with multi-fingered robot hands promises human-level dexterity, but collecting large-scale dexterous robot hand data remains diff

safetyarxiv-cs-ro

One Model, Many Graphs: Learning over Attributed Graphs across Heterogeneous Modalities with Vision-Language Models

arXiv:2607.19128v2 Announce Type: replace Abstract: Vision-language models (VLMs) provide a unified representation space for textual and visual information, yet their potential as general-purpose back

Online Non-Monotone DR-Submodular Maximization Matching the Offline 0.401 Factor

arXiv:2609.02145v1 Announce Type: cross Abstract: We study online maximization of nonnegative, non-monotone DR-submodular functions over compact convex down-closed subsets of the d-dimensional unit cu

Local Ai

Online Reinforcement Learning in the Met Office Unified Model through Distributed Model-Agent Coupling

arXiv:2609.02566v1 Announce Type: new Abstract: Machine-learnt corrections can complement numerical weather prediction only if they adapt to the evolving model state while preserving dynamical consist

local-aiarxiv-cs-lg

OR-Transformer: Scaling Real-Time Decision-Making to 1,000 Items

arXiv:2609.01933v1 Announce Type: new Abstract: Modern supply chain operations can require coordinating replenishment across thousands of heterogeneous items under correlated stochastic demand, hetero

Oracle, will I ever learn? A study of prediction convergence and complementarity across link prediction models

arXiv:2609.02638v1 Announce Type: new Abstract: Knowledge graphs have become an important source of structured knowledge for Web applications, including search, question answering, and recommender sys

tutorialsarxiv-cs-lg

ORB-SVM : An Innovative Hybrid Framework for Efficient Brain Tumor Detection from MRI Scans

arXiv:2609.02333v1 Announce Type: cross Abstract: Brain cancer remains one of the most significant challenges in modern medicine, where the accuracy of early stage diagnosis is a decisive factor in pa

Orthogonal Ensembles and Tested Explanations for Performer-Independent Body-Motion Emotion Recognition

arXiv:2609.02510v1 Announce Type: new Abstract: We study body-only, 12-class acted-emotion classification from skeleton motion under leave-performer-out (LPO) evaluation, a hard, underdetermined setti

safetyarxiv-cs-cv

OSDAG: Online Scheduling for Efficient Multi-Robot Collaboration

model-releasesarxiv-cs-ro

arXiv:2606.15255v2 Announce Type: replace Abstract: Coordinating heterogeneous multi-robot systems (MRS) for complex, long-horizon tasks requires both flexible high-level reasoning and efficient execu

OutageDiT: A Generative Foundation Model for Power Outage Forecasting and Scenario Simulation

arXiv:2609.01896v1 Announce Type: cross Abstract: Power-outage planning requires scenarios before an event occurs. These scenarios must represent uncertainty in magnitude, timing, and duration while p

Pailitao-MMSearch: Building Native E-Commerce Multimodal Search Foundation

arXiv:2607.17499v2 Announce Type: replace Abstract: The evolution of e-commerce has fundamentally transformed how users search for products, shifting from simple text-based keyword queries to complex

PaperCompiler: Faithful Paper-to-Code Generation via Repository-Level Specification Compilation

arXiv:2609.02272v1 Announce Type: cross Abstract: Faithfully translating research papers into repository-level implementations remains challenging because papers often describe methods at a high level

Passivity-Centric Safe Reinforcement Learning for Contact-Rich Robotic Tasks

arXiv:2503.00287v3 Announce Type: replace Abstract: Reinforcement learning (RL) has achieved remarkable success in various robotic tasks; however, its deployment in real-world scenarios, particularly

safetyarxiv-cs-ro

PEARL: Path-Entity Aligned Relational Learning with Contextual Subgraphs for Inductive Knowledge Graph Completion

arXiv:2609.02216v1 Announce Type: new Abstract: Inductive knowledge graph completion (IKGC) aims to predict missing links involving entities unseen during training, requiring models to learn transfera

tutorialsarxiv-cs-ai

Perceptually Regularized Diffusion Model for Image Super-Resolution

model-releasesarxiv-cs-cv

arXiv:2609.02016v1 Announce Type: cross Abstract: Image super-resolution, which aims to reconstruct high-resolution images from their low-resolution observations, is fundamental to medical imaging, re

Percolation Dynamics in Optimization : Variance Cascades and Discrete Scale Invariance

arXiv:2609.02373v1 Announce Type: cross Abstract: We study the dynamics of Stochastic Gradient Descent (SGD), which is known to steer deep neural networks toward invariant sets that correspond to simp

Persistent Sparse Autoencoders: Learning Feature-Specific Timescales in Language Model Representations

arXiv:2607.17117v2 Announce Type: replace-cross Abstract: Sparse autoencoders (SAEs) decompose language model activations into sparse features, yet these models traditionally encode each token indepen

tutorialsarxiv-cs-cl

PGPO: Potential-Guided Policy Optimization for Multi-Turn Agentic Tasks

arXiv:2609.02236v1 Announce Type: new Abstract: Group-based reinforcement learning (RL) has become an effective paradigm for LLM post-training, but in multi-turn agentic tasks with sparse terminal rew

safetyarxiv-cs-ai

PhoenixNest-Video: Evidence-Grounded Multimodal Agent Framework for Automated Video Interview Assessment

arXiv:2609.02231v1 Announce Type: new Abstract: Interview assessment requires per-criterion judgments grounded in behavioral evidence, yet surging applicant volumes have made human-only evaluation cos

safetyarxiv-cs-ai

Physics-Driven Independent Pair Generation for Iterative Self-Supervised Low-Dose CT Denoising

arXiv:2609.02654v1 Announce Type: new Abstract: Low-dose computed tomography (LDCT) measurements contain mixed Poisson-Gaussian noise. However, most self-supervised methods rely on generic image stati

tutorialsarxiv-cs-cv

PIE-APT: Abductive Planning over Temporal Dynamic Knowledge Graphs via Incremental Reasoning

arXiv:2607.27287v2 Announce Type: replace Abstract: Planning over Temporal Dynamic Knowledge Graphs (TDKGs) presents theoretical challenges in open-world environments with incomplete information. Exis