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arXiv:2609.22611v1 Announce Type: new Abstract: Humanoid robots can acquire complex skills by imitating kinematic humanoid motion references, yet reliable references for contact-rich interactions rema

agentsarxiv-cs-ro

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Agents

High-Dimensional Online Change Point Detection with Adaptive Thresholding and Interpretability

DGX agent

arXiv:2609.24278v1 Announce Type: new Abstract: Change point detection (CPD) identifies abrupt and significant changes in sequential data, with applications in human activity recognition, financial ma

agentsarxiv-cs-lg

22 Sept 2026

High-resolution Nitrogen Dioxide Maps Reveal Exposure Limit Breaches across Europe

arXiv:2609.24634v1 Announce Type: new Abstract: Nitrogen dioxide (NO2) is a common air pollutant, released into the atmosphere through the incomplete burning of fossil fuels, and associated with respi

Highly-Efficient Differentiable Simulation for Robotics

model-releasesarxiv-cs-ro

arXiv:2409.07107v3 Announce Type: replace Abstract: Robotics simulators have improved significantly in computational speed and scalability, enabling them to generate years of simulated data for comple

Hardware

HiLo-Token: Input-Adaptive High-Low Frequency Token Compression for Efficient Image Editing

arXiv:2606.13898v2 Announce Type: replace Abstract: Creative image editing tools, such as Photoshop's Remove or Generative Fill buttons, are central to everyday customer use and account for a major sh

hardwarearxiv-cs-cv

HOIBlender: Blending Lightweight Detection with Vision-Language Priors for Efficient Human-Object Interaction Detection

arXiv:2609.23431v1 Announce Type: new Abstract: Human-object interaction (HOI) detection requires grounding an interacting human-object pair and recognizing the verb that links them, often under sever

Holographic generative flows with AdS/CFT

arXiv:2601.22033v2 Announce Type: replace Abstract: Holography, in the form of the anti-de Sitter/conformal field theory (AdS/CFT) correspondence, offers a natural setting for generative modelling. Da

Horizon-Aware Early Event Prediction for Tokamak Disruption Alarms

arXiv:2609.24443v1 Announce Type: cross Abstract: Reliable disruption prediction is essential for the safe operation of future tokamaks. Existing full-distribution survival methods model the complete

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning?

arXiv:2412.07813v4 Announce Type: replace-cross Abstract: To alleviate the training burden in federated learning while enhancing convergence speed, Split Federated Learning (SFL) has emerged as a prom

Human-Level Accuracy, Non-Human Strategies: Revealing Model-Human Divergence in Video Physical Reasoning

arXiv:2609.22788v1 Announce Type: new Abstract: Video foundation models now reach human-level accuracy on physical-reasoning benchmarks, yet such tasks require predicting unobserved physical outcomes.

Human-LLM Deliberation as Interactive Proof: Conditions for Verifiability Without Transparency

arXiv:2609.24895v1 Announce Type: new Abstract: When an LLM supplies an argument that a user could not readily construct, how can the user decide whether to accept its claim? Inspired by interactive p

researcharxiv-cs-cl

HumanAgencyBench: Scalable Evaluation of Human Agency Support in AI Assistants

arXiv:2509.08494v2 Announce Type: replace-cross Abstract: As humans delegate more tasks and decisions to artificial intelligence (AI), we risk losing control of our individual and collective futures.

researcharxiv-cs-cl

HumynexSurg-1: A Curated Expert Liposuction Dataset

arXiv:2609.23885v1 Announce Type: cross Abstract: Robot foundation models learn manipulation from large demonstration corpora, but surgery is missing from those corpora: across the 780-hour Open-H sur

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

safetyarxiv-cs-ro

Hybrid Uncertainty Sensitivity Analysis Based on the HSIC for High-Dimensional Responses with Aleatory--Epistemic Separation

arXiv:2606.14053v2 Announce Type: replace-cross Abstract: Quantifying the influence of hybrid aleatory and epistemic uncertainties on high-dimensional system responses remains a major challenge in glo

HybridFlow: A 2-NFE Generative Policy for Real-Time Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2602.13718v2 Announce Type: replace Abstract: Generative policies for robotic manipulation must balance action accuracy with inference latency. We present HybridFlow, a three-stage policy infere

HyperCLIP++: Fine-tuning CLIP forOpen-vocabulary Semantic Segmentation in Hyperbolic Space

arXiv:2609.24564v1 Announce Type: new Abstract: CLIP, a foundational vision-language model, has emerged as a powerful tool for open-vocabulary semantic segmentation. While freezing CLIP's text encoder

Identifying Representational Biases in Datasets Using PCA: A Max-Disparity Partition Framework

arXiv:2609.24556v1 Announce Type: cross Abstract: Principal Component Analysis (PCA) minimises aggregate reconstruction error, which can inadvertently represent majority subgroups with substantially h

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

applicationsarxiv-cs-cv

Agents

Identity Continuity in Long-Term Embodied AI Relationships: From Agent-Specific Identity Representation to Identity-Continuity Appraisal

arXiv:2609.23356v1 Announce Type: cross Abstract: Long-term embodied AI will undergo learning, model updates, memory compression, hardware repair, and migration across embodiments. For users who have

agentsarxiv-cs-ro

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

applicationsarxiv-cs-lg

Local Ai

If You Hear It, Help Find It: Orthogonal Knowledge Distillation for Open-Vocabulary Audio-Visual Event Localization

arXiv:2609.23376v1 Announce Type: cross Abstract: Open-vocabulary audio-visual event localization (OV-AVEL) grounds a text-queried event in time from video, audio, and language. The supervision source

local-aiarxiv-cs-cv

ILRR: Inference-Time Steering Method for Masked Diffusion Language Models

arXiv:2601.21647v2 Announce Type: replace Abstract: Discrete Diffusion Language Models (DLMs) offer a promising non-autoregressive alternative for text generation, yet effective mechanisms for inferen

researcharxiv-cs-cl

Agents

Image Frame Dynamic Object Segmentation and Ego Motion Estimation using Radar Image Fusion

arXiv:2609.22857v1 Announce Type: new Abstract: Dynamic object segmentation and ego-motion estimation are closely coupled problems in autonomous driving, as accurate ego-motion estimation typically re

agentsarxiv-cs-cv

Imagine-RL: Residual-Confidence-Guided Cross-Attention for World-Model-Augmented VLA Reinforcement Learning

arXiv:2609.24033v1 Announce Type: new Abstract: Reliable action evaluation in contact-rich manipulation requires looking beyond the current observation to future visual and contact consequences. Exist

safetyarxiv-cs-ro

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

applicationsarxiv-cs-ro

Implementation of Quantum Implicit Neural Representation in Deterministic and Probabilistic Autoencoders for Image Reconstruction/Generation Tasks

arXiv:2603.06755v3 Announce Type: replace Abstract: We propose a quantum implicit neural representation (QINR)-based autoencoder (AE) and variational autoencoder (VAE) for image reconstruction and gen

IMPLICIT-Bench: Measuring Implicit Bias in Text-to-Image Models under Neutral Prompts

arXiv:2609.24228v1 Announce Type: new Abstract: Text-to-image (T2I) models are typically evaluated for bias using slot-based templates such as ``a photo of a [profession]''. Such templates probe only

Improved Private Sparse Covariance Estimation with Multiscale Threshold Tests

arXiv:2609.22783v1 Announce Type: new Abstract: We study differentially private covariance estimation in operator norm for mean-zero sub-Gaussian distributions with unknown covariance support and at m

Improving Parameter Utilization by Sharing Neural Experts Across Layers in Transformers

arXiv:2609.22199v1 Announce Type: new Abstract: Transformer-based large language models often suffer from inter-layer parameter redundancy, where functional transformations are redundantly learned acr

Improving the adaptive and continuous learning capabilities of artificial neural networks: Lessons from multi-neuromodulatory dynamics

arXiv:2501.06762v4 Announce Type: replace-cross Abstract: Continuous adaptive learning, the ability to adapt to the environment and keep improving performance, is a hallmark of natural intelligence. B

Incentive Noise and Structural Prior Infusion for Multi-modal Object Re-Identification

arXiv:2609.24539v1 Announce Type: new Abstract: Multi-modal object Re-Identification (ReID) benefits from complementary information across heterogeneous imaging modalities. To further enrich semantic

safetyarxiv-cs-cv

Increasing Skill Level Recruits Deeper Attention Layers in a Frozen Chess Transformer

arXiv:2609.23917v1 Announce Type: cross Abstract: Chess involves complex reasoning in a deterministic environment, which makes it a useful setting for studying the mechanisms of computation inside tra

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

applicationsarxiv-cs-lg

Industrial Kinematic Trajectory Model (IKTM): Coordinate-Free Autoregressive Generator

arXiv:2609.22173v1 Announce Type: new Abstract: Mobility simulation supports logistics, safety, and communications planning in industrial environments such as ports, mines, and airports. Existing traj

Infectious Bovine Pinkeye Detection Using Computer Vision and Imbalance-Aware Learning

arXiv:2609.23714v1 Announce Type: new Abstract: Infectious bovine pinkeye is a contagious ocular disease that adversely affects cattle health, welfare, and agricultural productivity. Conventional diag

researcharxiv-cs-cv

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

applicationsarxiv-cs-lg

Information-Directed Sampling for Causal Bandits

arXiv:2607.15577v2 Announce Type: replace Abstract: Causal bandits exploit structural relationships among variables to share information across interventions and accelerate the identification of high-

Information-Time Proximal Policy Optimization

arXiv:2609.24380v1 Announce Type: new Abstract: RLVR has substantially improved the reasoning capabilities of LLMs. However, existing methods typically parameterize temporal progression in the Markov

Initial Evaluation of Potential Bias in Coverage of Humans in Wikidata

arXiv:2609.22375v1 Announce Type: cross Abstract: Introduction. Open collaborative knowledge graphs such as Wikidata increasingly ground agentic artificial intelligence, information retrieval, and lan

safetyarxiv-cs-cl

InsertAnything: Generalizable Contact-Rich Precision Insertion from Simulation to Reality

model-releasesarxiv-cs-ro

arXiv:2609.24511v1 Announce Type: new Abstract: Contact-rich precision insertion is a key manipulation skill in robotic assembly. Tight clearances make insertion more sensitive to alignment errors and

INTCORT: Training-Free Spatial Reasoning Enhancement for Vision-Language Models via Input Transformations and Confidence Routing

arXiv:2609.24813v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have demonstrated remarkable capabilities in multimodal tasks, yet they still exhibit poor ability in spatial reasoning. E

researcharxiv-cs-cv

Intelligent Degradation Monitoring in Lithium-ion Batteries via Discharge Incremental Capacity Feature Estimation

arXiv:2609.22843v1 Announce Type: cross Abstract: Accurate and timely detection of degradation in lithium-ion batteries is crucial to ensure safety, reliability, and longevity in high-demand applicati

Tutorials

InterHier: Learning Interconnected Hierarchical Semantics for Open-Vocabulary Object Detection

arXiv:2609.24026v1 Announce Type: new Abstract: In this paper, we investigate the limitations of fixed, hand-crafted connectors in hierarchical semantic representations for open-vocabulary object dete

tutorialsarxiv-cs-cv

Interpretable Multi-Hypersphere Deep Anomaly Detection for Open-set Supervised Anomaly Detection

arXiv:2609.23008v1 Announce Type: new Abstract: Multi-class open-set anomaly detection requires a model to characterize the normal acceptance domain formed by multiple heterogeneous subdistributions u

Interpretable Stress Detection from ECG Signals Using Motif-Based Anomaly Analysis

arXiv:2609.22179v1 Announce Type: cross Abstract: Stress detection using physiological signals has gained significant attention due to its impact on both physical and mental health. While existing app

Is Imagination Derived from Hallucination? A Cross-Taxonomy Evaluation of Imagination and Hallucination in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2609.22152v1 Announce Type: new Abstract: Imagination performs as a high-level function of large language models (LLMs) which determines the potential of how an LLM creates unseen or creative co

iSDFT: Information-Proximal Self-Distillation for Continual Learning in LLMs

arXiv:2609.24646v1 Announce Type: new Abstract: On-policy self-distillation fine-tuning (SDFT) learns new skills from demonstrations while reducing forgetting, but it always distils toward the full de