Search: “industry”

THEIA: A Multimodal Dataset and Benchmark for Vision-Language Analysis of Layout

model-releasesarxiv-cs-lg

arXiv:2609.35035v1 Announce Type: new Abstract: The integration of artificial intelligence into computer-aided design frameworks has sparked a shift in the design of analog integrated circuits (ICs),

29 Sept 2026

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Agents

Bootstrapping Conversational Recommendation Agents At Spotify: Synthetic Data Generation and Self-Improvement Loops

DGX agent

arXiv:2609.30297v1 Announce Type: cross Abstract: Conversational recommendation agents are a new paradigm for content discovery, enabling users to express complex intents through natural language (e.g

agentsarxiv-cs-ai

28 Sept 2026

Local Ai

Distributed Learning as a Service: The Developer's Perspective

arXiv:2609.31061v1 Announce Type: new Abstract: Application developers of distributed learning services face challenges that a typical federated learning loop does not address. Specifically, the model

local-aiarxiv-cs-lg

REALMS: An AI-Assistant Conversational System for Real-Time Exact Audience Sizing over High-Dimensional Nested Profiles

arXiv:2609.30547v1 Announce Type: new Abstract: Audience sizing is a critical component of digital marketing. It enables precise resource allocation, campaign planning, and performance optimization. T

applicationsarxiv-cs-cl

Seasonal and Quantum-inspired Models for Neutron Monitor Time Series Forecasting

arXiv:2609.30281v1 Announce Type: new Abstract: We present a focused and reproducible study of multi-horizon forecasting on the Lomnicky Stit neutron monitor (LMKS) time series. Our evaluation suite c

T-RoPE: Time-Aware Rotary Position Embedding for Sequential Recommendation

arXiv:2609.30576v1 Announce Type: new Abstract: Large-scale recommenders increasingly adopt the sequential generative recipe behind large language models, bringing the Transformer into recommendation

safetyarxiv-cs-ai

What Will Remain Human in Software Architecture? A Focus Group Report

arXiv:2609.30334v1 Announce Type: cross Abstract: AI development agents are increasingly used to support and partially automate software architecture tasks. To explore how practitioners perceive this

AI-Moderated Interviews for Market Research and Digital Twins Calibration

arXiv:2609.29143v1 Announce Type: cross Abstract: AI-moderated interviews are emerging as a scalable market-research method for generating consumer insights and building consumer 'digital twins.' Yet

DCRMTA: Deep Causal Representation Learning for Multi-Touch Attribution

arXiv:2401.08875v3 Announce Type: replace-cross Abstract: Multi-touch attribution (MTA) is essential for estimating the contribution of individual advertising touchpoints to user conversions. While re

safetyarxiv-cs-ai

Tutorials

Let Training Guide Selection: Online Synthetic Data Filtering via Real-Anchored Utility

arXiv:2609.29988v1 Announce Type: new Abstract: Synthetic data can scale training supervision when real-world data are limited, but noise and distribution mismatch can reduce its value. Existing synth

tutorialsarxiv-cs-lg

Screen Before You Serve: Simulation for Production Customer Experience AI Agents at 140M Scale

arXiv:2609.30137v1 Announce Type: new Abstract: Customer experience (CX) agents use tools and large language models to address customer requests and guide conversational interactions with an organizat

agentsarxiv-cs-ai

A Resilience Recovery Method for Complex Traffic Network Security Based on Trend Forecasting

arXiv:2609.27903v1 Announce Type: new Abstract: Due to the rapid development of information technology, a huge and complex traffic network has been established across various sectors, including aviati

Discovery of fully efficient fault indicators along a data-based diagnosis process

arXiv:2609.28087v1 Announce Type: new Abstract: The integration of model-based and data-driven paradigms provides a powerful framework for fault diagnosis by combining the interpretability of analytic

Evaluating Open-Weight LLMs for Turkish Domain Documents Under Retrieval and Hardware Constraints

model-releasesarxiv-cs-cl

arXiv:2609.28007v1 Announce Type: new Abstract: Most Turkish-capable large language models (LLMs) are evaluated using general-purpose benchmarks rather than long, structurally complex domain documents

PASTABench: Proactive Assessment of Sequential Trajectories for Agent Safety

arXiv:2609.28197v1 Announce Type: new Abstract: As Large Language Models (LLMs) evolve into autonomous agents that alter real-world states, ensuring operational safety across multi-step workflows has

Predicting Activities in Aqueous Electrolyte Solutions with Hybrid Machine Learning

model-releasesarxiv-cs-lg

arXiv:2607.19114v2 Announce Type: replace Abstract: Activities in aqueous electrolyte solutions, usually described by ionic activity and osmotic coefficients, are important properties for modeling man

Pro-Bench: Prompt-Robust Open-Vocabulary Visual Grounding Across Real-World Heterogeneous Environments

model-releasesarxiv-cs-cv

arXiv:2609.27076v1 Announce Type: new Abstract: Open-vocabulary visual grounding enables robots to localise task-relevant entities from natural-language queries without dependence on predefined percep

Talk2Escape: Conversational Grounding for Vision-and-Language Navigation

arXiv:2609.28296v1 Announce Type: new Abstract: While Vision-and-Language Navigation (VLN) has demonstrated remarkable success, the prevailing single-turn paradigm exposes a fundamental vulnerability:

agentsarxiv-cs-ro

TNLearn: An Open Source Python Package for Task-based Neurons

arXiv:2609.27564v1 Announce Type: cross Abstract: The brain does not rely on a single type of neuron to perform all kinds of tasks; instead, it designs different neurons for different tasks. The conce

researcharxiv-cs-ai

Beyond Predictable Paths: Redefining AI Security Incident Reporting for Agents

arXiv:2609.24515v1 Announce Type: cross Abstract: AI agents are being deployed rapidly, accompanied by a growing number of AI-specific attacks and corresponding incidents. As incident reporting become

agentsarxiv-cs-ai

CoEvo: Oracle-Grounded Self-Evolution of a Single Model for Multi-Step Causal Reasoning

arXiv:2609.26094v1 Announce Type: new Abstract: Multi-step causal reasoning requires chaining inferences where each step constrains the next. An early error propagates silently, and a correct answer r

safetyarxiv-cs-lg

Explainable Recommendations at Scale: LLM Rationales for YouTube Music Artist Discovery

arXiv:2609.23877v1 Announce Type: new Abstract: Modern music streaming platforms face a persistent tradeoff: exploiting familiar content versus driving the exploration of novel items. While users freq

From Code to Requirements: Agentic Reverse Engineering of Business Rules at Enterprise Scale

arXiv:2609.22719v1 Announce Type: cross Abstract: Business requirements for enterprise software systems are rarely captured in structured form; the logic resides instead in source code, configuration

Incremental Consistency Execution for Autonomous Intelligent Systems

arXiv:2609.24090v1 Announce Type: new Abstract: Long-horizon autonomous intelligent systems rely on heterogeneous components such as large language models, databases, external APIs, and rule engines,

safetyarxiv-cs-ai

MirrorDistill: Illumination-Aware Latent Distillation for Efficient Low-Light Restoration

arXiv:2609.25331v1 Announce Type: new Abstract: Low-light image enhancement (LLIE) is an im- portant component of visual sensing systems operating under degraded illumination, including nighttime surv

safetyarxiv-cs-cv

Pinocchio: Fast Uncertainty Estimates for Black-Box Language Models

arXiv:2609.24881v2 Announce Type: new Abstract: In high-stakes decision-making applications of large language models (LLMs), practitioners require not only accurate LLMs but also uncertainty estimates

researcharxiv-cs-ai

Predictive Uncertainty for Neural CAE Surrogates

arXiv:2609.25430v1 Announce Type: new Abstract: Neural surrogates can substantially accelerate computer-aided engineering (CAE) workflows, but their use in design requires uncertainty estimates that r

RouteRLT: Learning When and Which RL Specialist Should Control a Vision-Language-Action Policy

arXiv:2609.26467v1 Announce Type: new Abstract: Vision-language-action (VLA) models provide broad manipulation competence, but often struggle during the precision-critical stages that dominate contact

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

applicationsarxiv-cs-ro

Collaborative Streaming Anomaly Detection with Interactive Explanations and Ensemble Consensus

arXiv:2609.23883v1 Announce Type: new Abstract: We present a collaborative streaming anomaly detection system for high-speed data streams that explicitly integrates human analysts into the decision lo

ContactDP: Contact-Guided Diffusion Policy for Tight Insertion Tasks

arXiv:2609.23800v1 Announce Type: new Abstract: High-precision connector insertion remains challenging for robotic systems due to tight mechanical tolerances, partial observability during contact, and

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

applicationsarxiv-cs-lg

General Collaborative Intelligence: Architecting Cognition for Resilient Multi-Agent Ecosystems

model-releasesarxiv-cs-cv

arXiv:2609.22967v1 Announce Type: new Abstract: Multi-agent unmanned systems are moving from isolated, ego-centric sensing toward collaborative intelligence, in which distributed agents exchange compa

GNN-based Path-aware multi-view Circuit Learning for Technology Mapping

arXiv:2601.14286v2 Announce Type: replace-cross Abstract: Traditional technology mapping suffers from systemic inaccuracies in delay estimation due to its reliance on abstract, technology-agnostic del

Hybrid Imitation Learning: Teleoperation Augmentation Primitives that Policies Learn to Trigger

arXiv:2512.04960v2 Announce Type: replace Abstract: What an operator can demonstrate bounds what imitation learning can learn. Teleoperation interfaces map the human body to the robot, so motions that

Local Ai

ServerlessLoRA: Enabling Low-Latency Serverless Multi-LoRA Serving

arXiv:2505.14468v2 Announce Type: replace Abstract: Multi-LoRA (Low-Rank Adaptation) serving allows many specialized LLM variants to share the same base model by attaching lightweight adapters. This m

local-aiarxiv-cs-lg

Yarn tracking of large-scale 3D textile reinforcements using topological material features

arXiv:2609.22315v1 Announce Type: new Abstract: Automated segmentation of CT images has become increasingly important to enhance the reliability of simulations through the generation of high fidelity

researcharxiv-cs-cv

OmniVBench: A Benchmark and Large-Scale Dataset for Omni Reference-to-Video Generation

model-releasesarxiv-cs-cv

arXiv:2609.22069v1 Announce Type: new Abstract: Reference-to-video (R2V) generation is evolving toward increasingly general and versatile reference control, giving rise to the emerging paradigm of omn

SABER: Learning Attention-based Semantic Affordance for Legged Locomotion

arXiv:2609.21572v1 Announce Type: new Abstract: Perceptive legged locomotion has advanced rapidly by integrating terrain geometry into learned policies, yet the integration of terrain meaning remains

TAPe+ML: A Compact Structured Representation for Multi-Task Computer Vision

arXiv:2609.20869v1 Announce Type: new Abstract: We present TAPe+ML v3, a compact computer vision system based on TAPe (Theory of Active Perception), a structured representation that encodes relations

researcharxiv-cs-cv

The Stochastic Shift: A New Evaluation Paradigm for Text-to-SQL with AI Operators

arXiv:2609.21133v1 Announce Type: cross Abstract: SQL has been augmented with AI operators, enabling modern data analytics platforms to derive insights from both structured and unstructured data. We o

researcharxiv-cs-ai

Towards Effective Visual-Inertial SLAM with Passive-Only Sensors for Low-Cost Autonomous Underwater Vehicles

model-releasesarxiv-cs-ro

arXiv:2609.21015v1 Announce Type: new Abstract: Improvements to Visual-Inertial Simultaneous Localization and Mapping (VI-SLAM) for low-cost autonomous underwater vehicles (AUVs) are critical for tran

A Generative-AI Modeling Framework for Explainable Decision Support in Complex Geosteering Scenarios

arXiv:2503.08509v2 Announce Type: replace Abstract: The real-time process of directional changes while drilling, known as geosteering, is crucial for hydrocarbon extraction and emerging directional dr

AI Smart Glasses for Wearable Intelligence: From Egocentric Sensing to Agentic Personalization

arXiv:2609.19793v1 Announce Type: new Abstract: Recent advances in artificial intelligence (AI) are reshaping smart glasses from egocentric capture and display devices into platforms for wearable inte

agentsarxiv-cs-cv

Compass-v3: Scaling Domain-Specific LLMs for Multilingual E-Commerce in Southeast Asia

model-releasesarxiv-cs-cl

arXiv:2509.09121v2 Announce Type: replace Abstract: Large language models (LLMs) excel in general-domain applications, yet their performance often degrades in specialized tasks requiring domain-specif

Detecting Deceptive Recruitment: A Signal-theoretic Machine Learning Framework for Early Identification of Labour Exploitation

arXiv:2609.20336v1 Announce Type: cross Abstract: Deceptive online job advertisements have emerged as a primary pathway into forced labour, yet systematic detection methods remain underdeveloped due t

applicationsarxiv-cs-lg

Perception, Layout, and Validation: Calibrated Confidence for Reliable Straight-Through Processing of Financial Documents

arXiv:2609.20110v1 Announce Type: new Abstract: Straight-through processing (STP) on extracted key-value fields from financial documents without human review requires a calibrated probability together

Semantic Layer Induction from Raw Telemetry via Hierarchical LLM and RAG Abstraction

arXiv:2609.19615v1 Announce Type: cross Abstract: Modern applications generate massive volumes of raw telemetry data, but translating those noisy, heterogeneous event streams into actionable business