Search: “applications”

Learning from Failure: Leveraging Unreliable Predictions in Semi-Supervised Real-World Adverse Weather Removal

arXiv:2610.02051v1 Announce Type: new Abstract: Adverse weather image restoration aims to recover images degraded by rain, haze, snow, and other weather-induced artifacts, thereby improving the robust

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Applications

Learning the identity: a case study of how SGD selects among functional decompositions

DGX agent

arXiv:2610.00615v1 Announce Type: new Abstract: One might think that learning the identity function with a deep linear residual network is trivial - the path along residual connections already impleme

applicationsarxiv-cs-lg

2 Oct 2026

Learning to Price Electricity for Optimal Demand Response

arXiv:2610.00755v1 Announce Type: cross Abstract: There is considerable interest in using time-varying electricity prices to shape consumer demand response, and better align energy demand with renewab

LineupRL: Verifiable Reinforcement Learning for Time Series Captioning via Caption-to-Series Identification

arXiv:2610.01800v1 Announce Type: new Abstract: Time series captioning is a fundamental step in time series understanding and can also serve as the bridge between signal and natural language. Supervis

Machine Translation for Sign Languages

arXiv:2610.00881v1 Announce Type: new Abstract: Sign language machine translation has progressed substantially over the past decade, evolving from isolated sign recognition to end-to-end translation s

Multi-Jurisdictional Legal Identity Assurance for Capability Gating: A Design-Science Proposal for Tiered, Reusable Identity Assurance of Natural, Juridical, and Machine Entities

arXiv:2610.00287v1 Announce Type: cross Abstract: Identity assurance is the cost a digital system pays for dishonesty and uncertainty: it exists to make acts attributable when not everyone can be trus

NarrativeFlow: Flow-Based Vision-Language-Action Model Using Robot Velocity Fields

arXiv:2610.00981v1 Announce Type: cross Abstract: We focus on language-conditioned flow-based manipulation, where robot flows (robot velocity fields) serve as embodiment-agnostic, motion-centric repre

Neither Black nor White: Balancing Semantic and Collaborative Signals with Graph-Informed Semantic IDs (GrIS)

arXiv:2610.01533v1 Announce Type: new Abstract: Existing work on Semantic IDs (SIDs) for generative recommendation treats SID construction as a representation learning problem: encode items into a qua

Not All Error Yields to Scale: Where Scaling Stops in Vision-Language Inference

arXiv:2610.01640v1 Announce Type: cross Abstract: Vision-language models (VLMs) face a fixed-budget trade-off between processing more visual information for fine-grained perception and using a larger

ODDR: One-Step Deshadow Diffusion via Reward Guidance

arXiv:2610.01291v1 Announce Type: new Abstract: Recent advances in deep learning for shadow removal have significantly enhanced image quality and realism. However, most approaches rely on real-world p

PyPottery: an AI-powered end-to-end suite for pottery processing and publication

arXiv:2610.02072v1 Announce Type: new Abstract: The study of ceramic materials constitutes a cornerstone of archaeological research, yet the post-production workflow for pottery documentation remains

Query-Conditioned Articulation Estimation from a Single Image

arXiv:2610.01726v1 Announce Type: new Abstract: Enabling robots to estimate the kinematic parameters of articulated objects unlocks a wide range of capabilities for interaction and manipulation. The e

Reformulation-Contrastive Learning for Mixed Integer Programs

arXiv:2610.00730v1 Announce Type: new Abstract: Mixed-integer linear programs (MILP) model many real-world decision problems, motivating machine-learning methods that exploit recurring structure to ac

Report: Amazon to offload $8B worth of AI chips, lease them back

Amazon.com Inc. reportedly plans to offload some of its artificial intelligence chips and then lease them back. The Financial Times today cited sources as saying that the transaction would involve a s

applicationssiliconangle

Rethinking Anonymity Claims in Synthetic Data Generation: A Model-Centric Privacy Attack Perspective

arXiv:2601.22434v2 Announce Type: replace-cross Abstract: Training generative machine learning models to produce synthetic tabular data has become a popular approach for enhancing privacy in data shar

ScaffoldM3C: A Multimodal Sequential Monte Carlo Framework for Generative Stable Construction Planning

arXiv:2610.00487v1 Announce Type: cross Abstract: Autonomously constructing physically realizable 3D structures remains a significant challenge due to combinatorial action spaces, interchangeable comp

Agents

Sharing some notes from OpenAI DevDay in parts. The first part matters, since it's on everyone's mind. How do you optimize for cost and perf…

Sharing some notes from OpenAI DevDay in parts. The first part matters, since it's on everyone's mind. How do you optimize for cost and performance? If you are building agentic applications today, the

agentsdair-ai--x

ShelfChange3D: Object-Level 3D Change Detection for Retail Shelf Monitoring

arXiv:2610.01283v1 Announce Type: new Abstract: Reliable shelf monitoring is an important capability for retail automation, yet existing out-of-stock detection methods mainly operate in image space an

ShowerFlex: Achieving Pseudo-Static Balancing in a Continuum Shower Hose

arXiv:2610.00936v1 Announce Type: new Abstract: With the global population rapidly aging, maintaining independence in Activities of Daily Living (ADLs), particularly bathing or showering, has become a

STCFormer: Adaptive Spatio-Temporal Modeling with Dynamic Cluster Transformer for Station-based Weather Forecasting

arXiv:2610.00377v1 Announce Type: new Abstract: Station-based weather forecasting supports daily life and economic activity, yet accurate forecasts require modeling complex spatial dependencies among

StoCFL: A Stochastically Clustered Federated Learning Framework for Non-IID Data with Dynamic Client Participation

arXiv:2303.00897v2 Announce Type: replace Abstract: Federated learning is a distributed learning framework that takes full advantage of private data samples kept on edge devices. In real-world federat

Model Releases

The Impact of Processing Parameters on High-Accuracy Measurements in UAV Photogrammetry

model-releasesarxiv-cs-cv

arXiv:2610.01438v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) photogrammetry is increasingly used in applications requiring high accuracy, such as determining ground surface changes ca

They stole your money and they’re proud of it. Each one of them broke the law.

They stole your money and they’re proud of it. Each one of them broke the law. NEW: President Trump directly told Russ Vought to find the funds to finance the ads glorifying him. The agency’s general

applicationsanthropic--x

TouchTherm: Building Multimodal Digital Twins of Objects for Tactile and Thermal Rendering

arXiv:2610.01943v1 Announce Type: new Abstract: Robotic simulation and virtual reality increasingly require object assets that capture not only visual geometry but also the physical cues underlying ta

Towards a Cloud Fog Edge System for Smart Building

arXiv:2610.01647v1 Announce Type: cross Abstract: In this article, we present our vision and recent advancements toward creating a decentralized system capable of learning from real-time data within b

UniTrackPLA: Unified Panorama-Language-Action Model for Instruction-Guided Navigation and Dynamic Person Tracking

arXiv:2610.00878v1 Announce Type: cross Abstract: General-purpose embodied robots should support both navigation toward language-specified destinations and dynamic person tracking under arbitrary init

Walking the Embedding Space: Datastore Extraction from Multimodal RAG

arXiv:2610.01871v1 Announce Type: cross Abstract: Multimodal Retrieval-Augmented Generation (MRAG) has emerged as a reliable and cost-effective technique of grounding the generative capabilities of Mu

“We find that on medium-length, well-defined accounting tasks, frontier AI models are now faster and more accurate than junior accountants, …

applicationsethan-mollick--x

“We find that on medium-length, well-defined accounting tasks, frontier AI models are now faster and more accurate than junior accountants, even the best one in our study.” Eighteen months ago they sc

3D Software Synthesis Driven by Constraint-Expressive Intermediate Representation

arXiv:2507.18625v3 Announce Type: replace-cross Abstract: Graphical user interface (UI) software has undergone a fundamental transformation from traditional two-dimensional (2D) desktop/web/mobile int

Research

A strategic roadmap for an atomistic machine-learning ecosystem

arXiv:2609.39090v1 Announce Type: cross Abstract: Data-driven machine learning (ML) techniques have become an essential tool in many domains of science. Their application to atomistic simulations of m

researcharxiv-cs-lg

AI-driven law firm Arceus Legal raises $17M to move beyond contract work

Artificial intelligence-driven law firm Arceus Legal today disclosed that it has raised 17 million in funding to expand beyond the commercial contract work it started with. Arceus provides legal servi

applicationssiliconangle

Anthropomorphism in the age of Large Language Models: An overview of potential risks and mitigations

arXiv:2609.38486v1 Announce Type: cross Abstract: Large Language Models (LLMs) and more broadly Artificial Intelligence (AI) systems are often described and understood in human-like terms, a phenomeno

applicationsarxiv-cs-cl

BatSLAM 2.0: Sequence-Verified Sonar Place Recognition in a Robust Pose Graph

arXiv:2609.40085v1 Announce Type: cross Abstract: Echolocating bats can navigate dark and cluttered spaces using echolocation. Over a decade ago, BatSLAM showed that a robot with a biomimetic binaural

Research

Beyond Mode Collapse: Generating Diverse Synthetic Expert Conversations via Generative Flow Networks

arXiv:2609.38359v1 Announce Type: new Abstract: High quality synthetic data is central to post training LLMs for adaptive AI applications that represent the diverse expert strategies and decisions in

researcharxiv-cs-ai

Beyond Simulation: Retain-and-Repair Neural Operators for Real-World Adaptation

arXiv:2609.39387v1 Announce Type: new Abstract: Neural operators increasingly benefit from pretraining on numerical simulations, yet adapting them for real-world prediction remains challenging. We int

California AG Rob Bonta issues an investigative subpoena to OpenAI, as part of a broader inquiry into cybersecurity incidents and risks related to its AI models (Jaspreet Singh/Reuters)

Jaspreet Singh / Reuters: California AG Rob Bonta issues an investigative subpoena to OpenAI, as part of a broader inquiry into cybersecurity incidents and risks related to its AI models — California

applicationstechmeme

CDMD: A Cross-Dataset Mixed-Type Diffusion Model for Tabular Data

arXiv:2609.39124v1 Announce Type: new Abstract: Generative models for tabular data are typically trained separately for each dataset, limiting knowledge transfer and requiring the storage of many spec

CIDER-FM: Foundation Models for Causal Inference from Diverse Experimental Regimes

arXiv:2609.39523v1 Announce Type: new Abstract: Causal foundation models (CFMs) amortise causal inference over priors of synthetic structural causal models (SCMs), predicting the effect of an experime

Coral Grow-out Robotic Assessment System (CGRAS): Scaling Coral Recruit Monitoring Through Robotics and Computer Vision

arXiv:2609.38846v1 Announce Type: new Abstract: Climate change is the largest threat to coral reefs, with increasing global impacts accelerating the need for scalable reef restoration technologies. La

DCM-SAM: Defect-Conditioned Mixture of LoRA Experts for NPU-Deployed AM Defect Segmentation

arXiv:2609.38811v1 Announce Type: new Abstract: Metal additive manufacturing parts are inspected by X-ray computed tomography, where labelled data is scarce, the pores and inclusions that matter span

Draft: A Parametric Tool for Robot Design Exploration

arXiv:2609.38405v1 Announce Type: new Abstract: Robot performance is often limited by the cost of iterating on morphology and control together, since every computer-aided design (CAD) change has to be

Eulerian Motion Reconstruction for Water Scenery

arXiv:2609.38622v1 Announce Type: new Abstract: Reconstructing and animating water scenery from nature produces compelling and immersive visual experiences. Previous work examined this task from the p

Exploiting Vulnerabilities: Universal Adversarial Attacks on Vision-Language-Action Models in Robotics

arXiv:2609.39178v1 Announce Type: cross Abstract: Recently, Vision-Language-Action (VLA) models have revolutionized robotic manipulation by seamlessly integrating visual perception, language understan

From Spectra to Joint Schedules in LLM Pre-training: 3+3(+2) Scaling-Law Regimes

arXiv:2609.40148v1 Announce Type: new Abstract: Power-law learning curves are often treated as fixed properties of a model and its data, although learning-rate and batch-size schedules can change the

From Tweets to Trades: Analyzing the Influence of Public Mood over Stock Market Performance in Turkiye

arXiv:2609.40064v1 Announce Type: new Abstract: Purpose: This study examines whether domain-specific public mood is associated with stock-market dynamics and whether these relationships vary across co

applicationsarxiv-cs-cl

Generative AI Purpose-built for Social and Mental Health: A Real-World Pilot

arXiv:2511.11689v4 Announce Type: replace-cross Abstract: Generative AI chatbots built for mental health could extend access to care, but evidence from real-world use is limited. We report a single-ar

Ghost in the Encoder: Decodable Artist Identity Representations in Lyrics-to-Song Generation

arXiv:2609.39552v1 Announce Type: cross Abstract: Text-to-song generation models can be prompted to imitate specific artists or regurgitate entire songs from their training data. Although these phenom

Gromov-Wasserstein Distillation for Inductive Multi-View Embedding

arXiv:2609.40047v1 Announce Type: new Abstract: Gromov-Wasserstein multidimensional scaling (GW-MDS) learns low-dimensional representations from relational data but remains transductive, providing no