applications

Deep Persona: A Psychologically Grounded Architecture and Evaluation Framework for Role-Playing Agents and Simulations

arXiv:2609.22255v1 Announce Type: new Abstract: Existing approaches to persona simulation with Large Language Models (LLMs) mostly rely on shallow character descriptions that fail to sustain coherent

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Diagnose, Then Repair: A Two-Stage MQM-Guided Post-Editing Framework for Domain-Specific Machine Translation

DGX agent

arXiv:2609.22793v1 Announce Type: new Abstract: LLM-based machine translation evaluation can closely match human judgments, but in practice it remains largely diagnostic, with the signals rarely trans

applicationsarxiv-cs-cl

22 Sept 2026

Directing large language models to follow the letter or spirit of the law

arXiv:2609.23083v1 Announce Type: new Abstract: The distinction between the spirit and letter of the law is a central issue across research and everyday life, and a growing concern for building safe,

Do Chess Explanations Reflect Model Decisions? Behavioral and Token-Level Tests of LLM Reasoning Faithfulness

arXiv:2609.22245v1 Announce Type: new Abstract: Large language models can produce fluent explanations for chess moves, but plausible language does not necessarily reflect the reasoning behind a decisi

Efficient K-generalizable Learned Search

arXiv:2603.06159v2 Announce Type: replace-cross Abstract: Learned top-K search improves the accuracy-latency trade-off of graph-based vector search, but existing methods are designed for a fixed K: se

Elevator-VIGS: Separating Elevator Motion from Robot Motion in Visual-Inertial Gaussian Splatting SLAM

arXiv:2609.23491v1 Announce Type: new Abstract: We present Elevator-VIGS, a visual-inertial 3D Gaussian Splatting SLAM system that keeps tracking and mapping through elevator rides. Inside a moving el

ERUPT: An Open Toolkit for Interfacing with Robot Motion Planners in Extended Reality

arXiv:2510.02464v2 Announce Type: replace Abstract: We present the Extended Reality Universal Planning Toolkit (ERUPT), an extended reality (XR) system for interactive motion planning. This paper serv

Exclusive: Darktrace makes SECURE AI generally available to monitor enterprise AI use

U.K.-based cybersecurity company Darktrace Holdings Ltd. today made its SECURE AI offering generally available, bringing its behavioral detection approach to corporate use of artificial intelligence t

applicationssiliconangle

Falling Trees: A Model Class for Interpretable Risk Prioritization

arXiv:2609.23780v1 Announce Type: new Abstract: Many real-world decisions require prioritizing high-risk cases, such as clinicians prioritizing high-risk patients before lower-risk ones. Falling rule

GARO: Geometry-Aware Redundancy Optimization for Real-Time and High-Fidelity Dynamic Gaussian Splatting

arXiv:2609.23509v1 Announce Type: new Abstract: Novel view synthesis is a key task for dynamic scene reconstruction, where high rendering speed is essential for applications such as virtual reality. E

Generalized Multimodal Foundation Model

arXiv:2609.22107v1 Announce Type: cross Abstract: Making prediction with multimodal data is widely used in diverse scenarios. Existing multimodal fusion models, once deployed, can only handle predefin

GPT-6 Sol and Luna roll out today in ChatGPT Work and Codex for Plus, Pro, Business, Enterprise, and Edu users. Both are also available in t…

GPT-6 Sol and Luna roll out today in ChatGPT Work and Codex for Plus, Pro, Business, Enterprise, and Edu users. Both are also available in the API. Free and Go users can try GPT-6 Luna in the desktop

applicationsopenai--x

Heidi Health nabs $340M to deepen adoption of AI agents within health systems globally

Heidi Health Trading Pty Ltd., a healthcare artificial intelligence startup, today announced it has raised a total of 340 million in new funding to support the company’s next phase of growth and deepe

applicationssiliconangle

Hessian Rank Constraint for Learning Structure of Nonlinear Latent Variable Models

arXiv:2609.24241v1 Announce Type: new Abstract: Uncovering latent variables and their causal relations from observed data is a fundamental yet challenging problem. Existing methods often rely on restr

Heterogeneous Robot Collaboration in Unstructured Environments with Grounded Generative Intelligence

arXiv:2510.26915v2 Announce Type: replace Abstract: While heterogeneous teams have typically been designed for well-specified missions with known semantics, generative intelligence, i.e., large langua

Identity-Consistent Analysis of Long-Shot Windsurfing Video: A Domain-Specific Offline Tracking System

arXiv:2609.24492v1 Announce Type: new Abstract: Long-shot windsurfing video combines small targets, large camera pans, prolonged overlaps, and rapidly changing backgrounds. The desired output is not a

IDProxy: CTR Prediction with Multimodal LLMs for Cold-Start Recommendation at Xiaohongshu

arXiv:2603.01590v2 Announce Type: replace-cross Abstract: Content-driven platforms such as Xiaohongshu often leverage click-through rate (CTR) prediction models for recommendation. However, these mode

Imagine then Verify: Affordance-Targeted Active Perception for Task-Oriented Grasping in Cluttered Scenes

arXiv:2609.23504v1 Announce Type: new Abstract: Task-oriented grasping (TOG) requires robots to grasp functional parts of objects (e.g., the handle of a mug for pouring), yet these affordance regions

Inductive Graph Representation Learning with Quantum Graph Neural Networks

arXiv:2503.24111v4 Announce Type: replace-cross Abstract: Graph Neural Networks (QGNNs) offer a promising approach to combining quantum computing with graph-structured data processing. While classical

Inference of Unknown Dynamical Components Using Next Generation Reservoir Computing: From Chaotic Systems to Climate Data

arXiv:2609.24754v1 Announce Type: new Abstract: We investigate next generation reservoir computing (NGRC) as a data-driven approach for inferring unseen components of dynamical systems. We compare NGR

Large language models in medical time series analysis

arXiv:2609.22262v1 Announce Type: cross Abstract: Medical time series (MedTS), including electrocardiograms (ECG), electroencephalograms (EEG), photoplethysmography (PPG), and vital-sign recordings, a

Learning-Based 3D Reconstruction of Power Networks from Aerial Point Clouds

arXiv:2609.23915v1 Announce Type: cross Abstract: This paper presents an end-to-end framework for reconstructing overhead power utility network topology and extracting span-level physical metadata fro

Machine Learning for Invisible Dark Boson Searches at the Electron-Ion Collider

arXiv:2609.22484v1 Announce Type: cross Abstract: We investigate whether adding t, the positive magnitude of the squared nuclear four-momentum transfer, enables boosted decision trees (BDTs) to improv

Macro-Scale Electrostatic Origami Motor

arXiv:2601.21976v2 Announce Type: replace Abstract: Origami structures have been an active area of research due to their high volume-to-mass ratio, packability, and shape adaptability. Previously-deve

MechaTerp-TRACE: A Novel Approach for Component Ablation Analysis in Language Models

arXiv:2609.22163v1 Announce Type: new Abstract: Interpretability research on large language models has produced accounts of factual recall in feed-forward layers and of token relationships in self-att

Mobile Imaging Solutions for Medical Diagnosis: Trends and Applications

arXiv:2609.24814v1 Announce Type: new Abstract: Advances in processing power, camera technologies, and mobile image analysis have made smartphones and other mobile devices, such as laptops, increasing

MUSE: Dependency-Aware Adaptation of a Frozen Vision Backbone for Multivariate Time Series Forecasting

arXiv:2609.24441v1 Announce Type: new Abstract: Multivariate time-series forecasting is essential to many real-world applications. Recent large vision models (LVMs) offer a promising paradigm by trans

Optimal Multi-way Decision Trees for Stratified Sampling in Online Controlled Experiments

arXiv:2609.23308v1 Announce Type: new Abstract: Online controlled experiments, or A/B tests, are widely used to estimate causal effects on digital platforms. A central challenge is to improve experime

PAOLI: Pose-free Articulated Object Learning from Sparse-view Images

arXiv:2509.04276v3 Announce Type: replace Abstract: We present a method for modeling articulated objects from sparse images with unknown camera poses. Existing approaches require dense multi-view obse

PICID: Proof-Driven Clause Learning in Neural Network Verification

arXiv:2503.12083v3 Announce Type: replace-cross Abstract: Current Deep Neural Network (DNN) verifiers are typically designed to prioritize scalability over reliability. Reliability can be reinforced t

Preserving What Matters: Semantic Scaffolds Beyond Saturation in Summarization Evaluation

arXiv:2609.22603v1 Announce Type: new Abstract: Summarization ships in countless production systems, making model selection a routine decision that depends on measuring summary quality. Existing metri

Proximal Residual Value Functions for Consistent Planning and Real-Time Execution

arXiv:2609.23242v1 Announce Type: new Abstract: We study two-timescale decision systems in which a planning layer periodically supplies a continuation-value function to a real-time optimizer that allo

Quantifying Hidden Salt for Precision Healthcare: Sodium Assessment via Joint-Factor Retrieval and Chain-of-Thought Inference

arXiv:2609.22171v1 Announce Type: new Abstract: Precision healthcare, particularly for conditions like hypertension and cardiovascular disease, necessitates monitoring of dietary sodium intake. Howeve

RAILS: Retrieval-Augmented Incremental LLM Clustering at Scale

arXiv:2609.24464v1 Announce Type: new Abstract: Using a Large Language Model (LLM) as the clusterer at production scale is hard: prompts cannot hold the entire label space, and per-document serial pro

React When You Need To: Event-Triggered Asynchronous Inference for VLA Policies

arXiv:2609.22587v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models commonly predict action chunks, limiting their ability to react to environmental changes during execution. Existing

Re:CAP - Auditing Retrieval Coverage in Production RAG Pipelines

arXiv:2609.24122v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is hard to monitor in production: exhaustive relevance labels do not exist for non-stationary multi-million-passage

SAIL: Test-Time Scaling for In-Context Imitation Learning with VLM

arXiv:2603.08269v2 Announce Type: replace Abstract: In-context imitation learning allows robots to acquire skills from demonstrations, yet one-shot trajectory generation remains fragile under environm

ScaleBlind: Point Cloud Completion under Unknown Scale

arXiv:2609.23404v1 Announce Type: new Abstract: Point cloud completion aims to infer a complete 3D shape from a partial point cloud and serves as a fundamental building block for downstream tasks such

See like a Robot: Robot-Centric Pointmaps for VLA Models

arXiv:2607.11498v2 Announce Type: replace Abstract: Vision-language-action (VLA) models require 3D spatial reasoning, yet RGB observations encode robot-object geometry only implicitly. Lifting depth w

SegTSim: A Big Data Driven Segmented Temporal Simulation Framework for Heterogeneous Multivariate Systems

arXiv:2609.22192v1 Announce Type: new Abstract: Heterogeneous multivariate time-series systems exhibit segment-specific nonlinear dynamics that challenge monolithic forecasting architectures. We propo

Simpler Methods Work Better for L1 Penalized Logistic Models and Large Datasets

arXiv:2609.23995v1 Announce Type: new Abstract: Linear models with an L_1-norm penalty remain state-of-the-art for high-dimensional (d > 1,000,000) tasks, offering a straightforward method for solving

Single Point, Full Mask: Velocity-Guided Level Set Evolution for End-to-End Amodal Segmentation

arXiv:2508.01661v2 Announce Type: replace Abstract: Amodal segmentation aims to recover complete object shapes, including occluded regions, serving as an essential technique for user-centric multimedi

SPID: Distilled Protein Backbone Generation

arXiv:2510.03095v4 Announce Type: replace Abstract: Diffusion- and flow-based generative models have recently demonstrated strong performance in protein backbone generation tasks, offering unprecedent

SRPR-Net: Semantic and Relational Prompt Refinement for Automated SAM-based Instance Segmentation

arXiv:2609.24226v1 Announce Type: new Abstract: Instance segmentation is a fundamental computer vision task with diverse real-world applications. Recently, prompt-driven foundation models have shown p

Stagewise Anomaly Detection for E-Transaxle Quality Monitoring Using Wavelet and STFT Features

arXiv:2609.22172v1 Announce Type: cross Abstract: This paper presents two interpretable machine-learning frameworks for quality screening of e-transaxle assemblies in electric vehicles: a Stagewise Wa

StateMem: Single-State Residual Memory with Adaptive Inference for Vision-Language-Action Policies

arXiv:2609.22684v1 Announce Type: cross Abstract: Memory-dependent robotic manipulation often requires later actions to use information from earlier interactions. Existing vision-language-action (VLA)

Steering Through Contact: A Finite-Support Motion Model for Single-Track Center-Articulated Robots

arXiv:2609.23271v1 Announce Type: new Abstract: Trajectory planning and control in field robotics rely on predicting how propulsion and steering affect vehicle motion when contact points undergo slip.

The Corroboration Illusion: When More News Makes LLM Forecasts Less True

arXiv:2609.22246v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to forecast real-world events by retrieving and reasoning over news. We show that this dependence on