applications

Lightweight Ranking Heads: Accelerating Multi-Task Experimentation in Production Recommender Systems

arXiv:2609.25433v1 Announce Type: new Abstract: Modern production-scale recommender systems rely on complex, multi-task ranking models. Introducing new prediction tasks into these massive systems ofte

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Marginal Log-Likelihood Increments under Dirichlet-Smoothed Markov Estimation

DGX agent

arXiv:2609.25675v1 Announce Type: new Abstract: For a Dirichlet-smoothed transition model, the effect of adding one workflow trace to the training archive is an exact change in reference-weighted log

applicationsarxiv-cs-lg

23 Sept 2026

Memory-Free Continual Learning with Null Space Adaptation for Zero-Shot Vision-Language Models

arXiv:2510.21175v2 Announce Type: replace Abstract: Pre-trained vision-language models (VLMs), such as CLIP, have demonstrated remarkable zero-shot generalization, enabling deployment in a wide range

Mirror Skin: In Situ Visualization of Robot Touch Intent on Robotic Skin

arXiv:2512.11472v3 Announce Type: replace-cross Abstract: Effective communication of robot touch intent is essential for safe and predictable physical human-robot interaction. While intent communicati

Moving6DPoSe: A Multimodal Database for Monocular 6D Pose Estimation and Segmentation of Moving Objects

arXiv:2609.26161v1 Announce Type: new Abstract: Estimating the 6D pose of moving objects remains challenging due to motion blur and the limited temporal resolution of conventional frame-based cameras.

MultiViewDx: Evidence-Linked Multi-View Clinical Diagnosis

arXiv:2410.14948v2 Announce Type: replace Abstract: Medical multimodal large language models (MLLMs) can perform well on existing medical visual question answering (MedVQA) benchmarks, but their train

applicationsarxiv-cs-cl

NeMo-map: Neural Implicit Flow Fields for Spatio-Temporal Motion Mapping

arXiv:2510.14827v3 Announce Type: replace Abstract: Safe and efficient robot operation in complex human environments can benefit from good models of site-specific motion patterns. Maps of Dynamics (Mo

Norm2Tex: Augmenting Visuo-Tactile Simulations with Texture

arXiv:2609.25398v1 Announce Type: new Abstract: Large-scale datasets are essential for training generalist robot control policies. Collecting real-world tactile data is costly and time-consuming, moti

Offloaded inference for real-world physical AI robotics

applicationsmicrosoft-research

Robots are getting smarter, but how can their hardware match that growth? New Microsoft Research findings show that moving AI inference beyond the robot can improve task success, boost efficiency, and

OV-MAP: Open-Vocabulary Zero-Shot 3D Instance Segmentation Map for Robots

arXiv:2506.11585v3 Announce Type: replace Abstract: We introduce OV-MAP, a novel approach to open-world 3D mapping for mobile robots by integrating open-features into 3D maps to enhance object recogni

Predicting Postprandial Glycemic Response from Meal Images, Clinical Variables, and Gut Microbiome Information

arXiv:2609.24453v1 Announce Type: new Abstract: Predicting postprandial glycemic response (PPGR) is fundamental to personalized nutrition and type 2 diabetes management, yet existing approaches typica

Quantum Model Parallelism for MRI-Based Classification of Alzheimer's Disease Stages

arXiv:2602.00128v2 Announce Type: replace Abstract: With increasing life expectancy, AD has become a major global health concern. While classical AI-based methods have been developed for early diagnos

Recovering Lost Details: Multi-Scale Frequency Compensation for Long-Term Time Series Forecasting

arXiv:2609.24229v1 Announce Type: new Abstract: Long-term time series forecasting has made significant progress by leveraging multi-scale information to capture hierarchical temporal patterns and mode

REDACT: Robust Perceptive Locomotion under Unseen Visual Corruption

arXiv:2609.25450v1 Announce Type: new Abstract: Depth-conditioned locomotion policies have demonstrated impressive agile maneuvers, but can be steered to unpredictable actions when observations are ou

Reinforcement Learning for Delivery Drone-Based Participatory Sensing in Dynamic Environments

arXiv:2607.18874v2 Announce Type: replace Abstract: Using Unmanned Aerial Vehicle (UAV) for urban sensing has emerged as a powerful paradigm to monitor the status of the city, e.g., air quality and no

Robust Photoplethysmography Signal Denoising via Mamba Networks

arXiv:2510.11058v2 Announce Type: replace Abstract: Photoplethysmography (PPG) is widely used in wearable health monitoring, but its reliability is often degraded by noise and motion artifacts, limiti

Signed Graph Pre-Training and Prompt Learning

arXiv:2609.25722v1 Announce Type: new Abstract: Signed graphs arise in trust--distrust networks, financial correlation systems, biological interaction graphs, and many other domains in which edges can

Skill Sequence Planning for Collaborative Multi-Robot Construction

arXiv:2609.25649v1 Announce Type: new Abstract: Robots have significant potential to automate construction processes. However, their industry adoption remains limited, partly because of the programmin

Smoothed Analysis of Inconsistent A*

arXiv:2609.23680v1 Announce Type: cross Abstract: The A* search is a fundamental path-finding algorithm in artificial intelligence. While admissible and consistent heuristics guarantee efficient perfo

Spatiotemporal Calibration of Doppler Velocity Logs for Underwater Robots

arXiv:2510.24571v2 Announce Type: replace Abstract: The calibration of extrinsic parameters and clock offsets between sensors for high-accuracy performance in underwater SLAM systems remains insuffici

Spatiotemporal Kronecker Covariance Neural Networks

arXiv:2609.25326v1 Announce Type: new Abstract: Multivariate time series contain complex patterns that span across both space and time. While covariance-based statistical tools like spatiotemporal Pri

StrataVLA: Hierarchical and Efficient 3D Geometric Grounding for Vision-Language-Action Models

arXiv:2609.26071v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models inherit strong semantic priors from large-scale vision-language pretraining, yet remain limited in robotic manipulat

Targeted Review for AI-Assisted Biodiversity Surveys: Active Continuous-Score Occupancy Modeling

arXiv:2609.25657v1 Announce Type: new Abstract: We increasingly use machine learning to label scientific datasets. The models we develop and deploy are improving all the time, but they are not and wil

The Cartesian Hand: In-Hand Manipulation with All-Linear Fingers

arXiv:2609.25696v1 Announce Type: new Abstract: Robotic manipulation has increasingly pursued human-like dexterous hands with many articulated degrees of freedom, offering rich manipulation capabiliti

The Challenge of Identifying the Origin of Black-Box Large Language Models

arXiv:2503.04332v2 Announce Type: replace-cross Abstract: The tremendous commercial potential of large language models (LLMs) has heightened concerns over their unauthorized use. To address this, we f

💯: “there is no AI-controlled robot that can do what a plumber can do, or what a capuchin monkey can do, because the physical world is much…

applicationsgary-marcus--x

💯: “there is no AI-controlled robot that can do what a plumber can do, or what a capuchin monkey can do, because the physical world is much more demanding than the world behind the screen. Passing the

Topological Signal Processing With Unoriented Operators

arXiv:2609.25310v1 Announce Type: new Abstract: Topological signal processing (TSP) processes signals on simplicial complexes with oriented boundary operators, which is the natural choice for flow sig

TTTIR: Unlocking Instance-Specific State Evolution via Test-Time Training for Image Restoration

arXiv:2609.26151v1 Announce Type: cross Abstract: Image restoration is inherently challenging due to the diverse and highly input-dependent nature of real-world degradations. While recent architecture

Ultra Strong Machine Learning: LLM-Generated Explanations Do Not Yet Suffice for Teaching Humans Active Learning Strategy

arXiv:2509.00961v3 Announce Type: replace-cross Abstract: Active learning is a general learning mechanism shared by artificial and human learners. Whether AI can teach humans such a strategy that tran

You Should Be Properly Scoring Your Odometry

arXiv:2609.25900v1 Announce Type: new Abstract: When we evaluate the performance of our odometry, it is common practice to score the estimated track against a ground truth. Unfortunately, scoring uses

A Comparative Framework for Evaluating Foundation Models on Tabular Data: A Case Study in Healthcare

arXiv:2609.22154v1 Announce Type: new Abstract: Tabular data is the most common format in clinical practice, encompassing laboratory results, medication records, diagnostic codes, and patient demograp

A Hybrid Quantum Neural Network to Analyse Big Experimental Powder X-ray Diffraction Data

arXiv:2609.22376v1 Announce Type: cross Abstract: Quantitative analysis of experimental powder X-ray diffraction data remains challenging when evaluating complex multiphase materials and noisy measure

A Recipe for Efficient Sim-to-Real Transfer in Manipulation with Online Imitation-Pretrained World Models

arXiv:2510.02538v2 Announce Type: replace Abstract: We are interested in solving the problem of imitation learning with a limited amount of real-world expert data. Existing offline imitation methods o

A Temporal Knowledge Graph for Music Festival Lineup Forecasting

arXiv:2609.24467v1 Announce Type: new Abstract: Music festival lineups emerge from complex relationships among artists, genres, releases, labels, and past performances, making the prediction of future

A Topological Representation with Object-Path Graphs for Open-Vocabulary Instance Navigation

arXiv:2609.24189v1 Announce Type: new Abstract: Vision-language navigation requires embodied agents to navigate environments using natural language instructions and visual observations. Existing appro

A Tunable Despeckling Neural Network Stabilized via Diffusion Equation

arXiv:2411.15921v3 Announce Type: replace Abstract: The removal of multiplicative Gamma noise is a critical research area in the application of synthetic aperture radar (SAR) imaging, where neural net

Accounting for Optimal Control in the Sizing of Isolated Hybrid Renewable Energy Systems Using Imitation Learning

arXiv:2601.03679v2 Announce Type: replace-cross Abstract: Decarbonization of isolated or off-grid energy systems through phase-in of large shares of intermittent solar or wind generation requires co-i

Anthropic and OpenEvidence partner to offer a specialized version of OpenEvidence's AI search tool for physicians in about 100 low- and middle-income countries (Nancy Lapid/Reuters)

Nancy Lapid / Reuters: Anthropic and OpenEvidence partner to offer a specialized version of OpenEvidence's AI search tool for physicians in about 100 low- and middle-income countries — Artificial inte

applicationstechmeme

Applications of Neural Cellular Automata: State of the Art, Challenges and Opportunities

arXiv:2609.24595v1 Announce Type: new Abstract: Neural Cellular Automata (NCAs) are a new type of neural network architecture which enable accurate and robust inference at extremely small model sizes.

Augmented Hypothesis Testing with Persona-Based LLM Simulations

arXiv:2609.24629v1 Announce Type: new Abstract: A/B testing requires large sample sizes, long timelines, and significant costs. When auxiliary predictions of experimental outcomes are available from m

Australian healthcare AI startup Heidi raised 340M, including a 100M Series C led by Blackbird at a 900M valuation, taking its total funding to 430M+ (Olivia Poh/Bloomberg)

Olivia Poh / Bloomberg: Australian healthcare AI startup Heidi raised 340M, including a 100M Series C led by Blackbird at a 900M valuation, taking its total funding to 430M+ — Heidi, an artificial int

applicationstechmeme

BayesianGS-SLAM: Uncertainty-Aware Neural Rendering SLAM via Probabilistic Formulation

arXiv:2609.24140v1 Announce Type: new Abstract: Neural-rendering-based SLAM relies on rendered RGB-D residuals for camera tracking and map optimization, but the reliability of these predictions can va

Behavior Trees for Robotic Systems: An Empirical Study on Practices and Experiences

arXiv:2609.22404v1 Announce Type: new Abstract: Over the last decade, behavior trees (BT) have become one of the dominant behavior models for coordinating missions of robotic systems. Yet empirical ev

CompVLA: A Variable Compliance Vision-Language-Action Model for Contact-rich Manipulation

arXiv:2609.23614v1 Announce Type: new Abstract: Contact-rich manipulation, requiring robots to regulate not only motion but also how they yield to external forces, has emerged as the next frontier for

Contextual Causality with Large Language Models: A Survey

arXiv:2609.22409v1 Announce Type: new Abstract: Understanding contextual causality is critical for large language models (LLMs), as it enables them to accurately identify causal relations in specific

applicationsarxiv-cs-cl

Contrastive Siamese Representation Learning for Predictive Maintenance of Electrical Submersible Pumps

arXiv:2609.22360v1 Announce Type: new Abstract: Electrical submersible pumps (ESPs) are essential in offshore oil production, where unexpected failures can result in significant operational and financ

Contributions to the hierarchy of probabilistic languages

arXiv:2609.23567v1 Announce Type: cross Abstract: We reconsider the theory of probabilistic formal languages generated by n-gram models and by probabilistic context-free grammars (PCFGs). The expected

applicationsarxiv-cs-cl

Decentralized Multi-Robot Exploration with Probabilistic Peer Intent and Multi-hop Plan Propagation

arXiv:2609.22726v1 Announce Type: new Abstract: Efficient coordination under limited communication remains a key challenge in decentralized multi-robot exploration. While centralized approaches benefi