Search: “papers”

Evaluating Accuracy and Probabilistic Reliability of Zero-Shot Time Series Foundation Models

arXiv:2609.25788v1 Announce Type: new Abstract: Time Series Foundation Models (TSFMs) promise a paradigm shift toward zero-shot forecasting by eliminating task-specific training. However, existing wor

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Evaluating the Effectiveness of SechKAN on 1D Data

DGX agent

arXiv:2609.25876v1 Announce Type: new Abstract: The connection between the Kolmogorov-Arnold representation theorem (KART) and neural network design has led to the development of Kolmogorov-Arnold Net

model-releasesarxiv-cs-lg

23 Sept 2026

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

applicationsarxiv-cs-ai

Fairly Compensated Distributed Information Retrieval and Augmentation for AI Agents

arXiv:2609.22601v1 Announce Type: cross Abstract: The increasing reliance of autonomous AI agents on external and distributed knowledge sources introduces a fundamental challenge for decentralized inf

safetyarxiv-cs-ai

Federating Quantum and Classical Computing: A Privacy-Preserving Hybrid Approach

arXiv:2609.25082v1 Announce Type: new Abstract: Quantum machine learning (QML) is increasingly recognized as one of the most promising near-term applications of quantum computing, viewed as a next-fro

Few-Shot Demonstrations Elicit the Use of In-Context World Representations in LLMs

arXiv:2609.24352v1 Announce Type: new Abstract: Large language models (LLMs), when acting as agents, are expected to take observed data in context, infer the latent state space underlying the world, a

agentsarxiv-cs-ai

Tutorials

FoMo: Forking Moment in Generative Trajectory as a Perceptual Distance

arXiv:2609.25716v1 Announce Type: new Abstract: Reference-based image quality assessment (IQA) metrics aim to reflect how humans perceive the perceptual distance between a pair of images. To learn how

tutorialsarxiv-cs-cv

From Capability to Assurance in Autonomous Penetration-Testing Harnesses: A Framework and Reference Implementation

model-releasesarxiv-cs-ai

arXiv:2609.22664v1 Announce Type: cross Abstract: Research on large language model agents for penetration testing is evaluated almost entirely by capability: whether the agent captures a flag or repro

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

model-releasesarxiv-cs-ai

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

From Inference Engine to Inference Control Plane: Connecting vLLM, llm-d, and the Evolution of Efficient Distributed LLM Serving

model-releasesarxiv-cs-ai

arXiv:2609.23130v1 Announce Type: new Abstract: Large language model (LLM) inference is evolving from an engine-local optimization problem into a distributed control problem involving reusable state,

From Instrument-Mounted Demonstrations to In-Vivo Execution: Learning Bimanual Laparoscopic Appendectomy Without Robot-Collected Demonstrations

model-releasesarxiv-cs-ro

arXiv:2609.25625v1 Announce Type: new Abstract: Most minimally invasive surgery is still performed with hand-held laparoscopic instruments, and the surgeon's instrument kinematics are lost when the op

From Research Frontier to Laboratory Bench: Design of a Four-Tier Experimental Teaching System for Multimodal Medical Image Intelligent Diagnosis

arXiv:2609.22790v1 Announce Type: new Abstract: Undergraduate programmes in intelligent medical engineering are expanding, yet laboratory curricula lag behind the multimodal, long-tailed, and distribu

safetyarxiv-cs-ai

Generative Embodied Multiple Behavior Control Systems for Human-like Agents

arXiv:2609.22691v1 Announce Type: new Abstract: An enduring and richly elaborated dichotomy in cognitive neuroscience is that of human behavior control mechanisms, divided into habitual versus goal-di

agentsarxiv-cs-ai

glance-vlm speedlab is now open source! read: https://glance.yohei.me/speed/ try: https://github.com/yoheinakajima/glance-speedlab turn any …

model-releasesyohei-nakajima--x

glance-vlm speedlab is now open source! read: https://glance.yohei.me/speed/ try: https://github.com/yoheinakajima/glance-speedlab turn any webcam into multiple live AI detectors (emotion, count, obje

Goal-driven Variant Categorization

arXiv:2609.22475v1 Announce Type: new Abstract: Process discovery rarely yields a single coherent process structure. For analysis, a common step is to cluster process variants based on structural simi

researcharxiv-cs-ai

HARMONY: Hierarchical Agentic Reasoning for MONocular Image-to-Scene Synthesis

arXiv:2609.26793v1 Announce Type: new Abstract: Compositional 3D scene reconstruction has recently been explored from two directions: agentic reasoning that provides semantic understanding of spatial

safetyarxiv-cs-cv

High-Bandwidth Biomimetic Finger for Tactile-Transparent Remote Texture Sensing

arXiv:2609.26256v1 Announce Type: new Abstract: High-fidelity tactile feedback is essential for robotic teleoperation, enabling precise manipulation and critical decision-making. While biomimetic fing

researcharxiv-cs-ro

Local Ai

High-Order Liquid Evidence Modeling for Continuous and Subtle GNSS Spoofing Detection in Autonomous Driving

arXiv:2609.26231v1 Announce Type: new Abstract: Continuous and subtle GNSS spoofing poses a serious threat to autonomous vehicles because forged positions may remain locally plausible while gradually

local-aiarxiv-cs-lg

Higher-Order Approximation of Exit Functionals in Sampling-Based Stochastic Model Predictive Control

arXiv:2609.25257v1 Announce Type: cross Abstract: Safety evaluation in sampling-based stochastic model predictive control often requires numerical estimation of exit functionals. The approximation of

ICDAR2026 Competition on Multimodal Reasoning over Documents in Multiple Domains

arXiv:2609.25055v1 Announce Type: new Abstract: In this report we present results of the ICDAR2026 Competition on Multimodal Reasoning over Documents in Multiple Domains. This competition aimed to adv

agentsarxiv-cs-cl

Tutorials

In-Context Guidance: Learning Inter-Task Synergies via Numerical Foundational Models for Few-Shot Multitask Optimization

arXiv:2609.25836v1 Announce Type: new Abstract: Multi-task optimization (MTO) addresses a set of optimization tasks simultaneously, often suffering from inaccurate inter-task relationship estimation u

tutorialsarxiv-cs-lg

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

Learning to Plan in Human-Robot Collaboration: Multimodal Reinforcement Learning for Adaptive Interaction

arXiv:2609.25274v1 Announce Type: new Abstract: Robot assistants for older adults and people with disabilities need to perform collaborative tasks with users effectively. The core component of these s

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

applicationsarxiv-cs-lg

Local Ai

LLM-Driven Training-free Location-Attribute Synergic Fusion: A Closed-Loop Paradigm for Dual-source Encrypted POIs and LULC Mapping

arXiv:2609.25051v1 Announce Type: new Abstract: Dual-source encrypted points of interest (DSEP), POIs from two encrypted coordinate systems, suffer from intertwined location and attribute uncertaintie

local-aiarxiv-cs-cl

Manipulation of Deformable Linear Objects Using Model Predictive Path Integral Control with Bidirectional Long Short-Term Memory Learning

arXiv:2609.26238v1 Announce Type: new Abstract: The manipulation of Deformable Linear Objects (DLOs) such as cables poses a significant challenge for automation due to their infinite degrees of freedo

researcharxiv-cs-ro

mbariml: a curation pipeline for turning deep-sea imagery and video into object-detection training data

arXiv:2609.25500v1 Announce Type: new Abstract: Training data quantity and quality greatly affect object detection model performance, regardless of model architecture. When using object detection mode

researcharxiv-cs-cv

Mean Velocity Matching: Rethinking Generative Dynamics in Diffusion Models

arXiv:2609.25444v1 Announce Type: new Abstract: This work studies prediction parameterization for stochastic generative dynamics in diffusion models. Existing velocity-based generative models provide

MGRL-RSCC: Multi-Granularity Reward Reinforcement Learning for Fine-Grained Remote Sensing Change Captioning

arXiv:2609.26166v1 Announce Type: cross Abstract: Remote Sensing Change Captioning (RSCC), which aims to generate accurate and detailed linguistic descriptions of ground object variations from bi-temp

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

Local Ai

Mitigating LLM Over-Refusal via Dynamic Semantic Routing Calibratione

arXiv:2609.25049v1 Announce Type: new Abstract: Large language models (LLMs) aligned for safety often suffer from over-refusal, incorrectly rejecting benign yet safety-related instructions. Prior stud

local-aiarxiv-cs-cl

Neighbor-Aware Token Reduction via Hilbert Curve for Vision Transformers

arXiv:2512.22760v2 Announce Type: replace Abstract: Vision Transformers (ViTs) have achieved remarkable success in visual recognition tasks, but redundant token representations limit their computation

researcharxiv-cs-cv

Peerify: Benchmarking Peer-Review Claim Verification

model-releasesarxiv-cs-cl

arXiv:2609.25046v1 Announce Type: new Abstract: Peer review plays a central role in scholarly publishing, yet verifying whether reviewer claims are supported by manuscript evidence remains a largely m

PermuFormer: Multi-Task Pretraining for Permutation Representation in Algebraic Combinatorics

arXiv:2609.25438v1 Announce Type: new Abstract: Diverse pretraining has been shown to be an effective method for learning reusable, domain-aware representations that provide a starting point for fine-

Physics-guided deep metric learning with continuous time embeddings for open-world radar pulse de-interleaving

arXiv:2609.25057v1 Announce Type: cross Abstract: Radar pulse de-interleaving is a foundational Electronic Support Measures (ESM) task that aims to separate chronologically interleaved pulse streams f

PP-Net: A Hybrid Physical-Prior Neural Network for Scattered Light Removal in Biomedical Images on Embedded Devices

arXiv:2609.26474v1 Announce Type: cross Abstract: Scattered light is common in biomedical images, yet its removal remains challenging. The difficulty arises from three aspects: first, aligned scattere

PreGS: A Parameter-Transfer-Based Multi-Expert Graph Neural Network for Node Classification

arXiv:2609.26310v1 Announce Type: new Abstract: Graph neural networks have achieved strong performance in node classification by aggregating information from graph neighborhoods. However, a single agg

PreUnlearn: Auditing Collateral Knowledge Damage Before Large Language Model Unlearning

arXiv:2606.18473v2 Announce Type: replace Abstract: Machine unlearning for large language models (LLMs) aims to remove specified knowledge while preserving the rest of the model's capabilities. Howeve

researcharxiv-cs-cl

RepUCB: Representation Learning-Based UCB for Heterogeneous Multi-Task Linear Bandits

arXiv:2604.00531v2 Announce Type: replace Abstract: Multi-task representation learning exploits the shared structure among related tasks by learning a common latent representation, thereby improving s

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

applicationsarxiv-cs-lg

SafeLoop: Risk-Aware Rollback for Vision-Language-Action Manipulation

arXiv:2609.26313v1 Announce Type: new Abstract: Recent vision-language-action (VLA) models are promising for general-purpose manipulation, but long-horizon execution remains fragile. Small state-estim

Safety-Constrained Model Predictive Control for an Omnidirectional Walking Assistive Robot Using Control Barrier Function

arXiv:2609.25994v1 Announce Type: new Abstract: Providing safe and effective mobility assistance plays a crucial role in restoring independence and enhancing the quality of life for individuals with m

Same Quantity, Different Answer: Numerical Representation Invariance in Language Models

model-releasesarxiv-cs-cl

arXiv:2609.25009v1 Announce Type: new Abstract: Numerically equivalent word problems should yield the same canonical answer whether a quantity is written as a decimal, fraction, percentage, number wor

Shaft-Configuration-Adaptive Catheter Tip Position Estimation via Motor-History Conditioned Residual Learning

arXiv:2609.26304v1 Announce Type: new Abstract: Tendon-driven continuum manipulators are widely used in medical applications, where accurate tip-position estimation is essential for precise navigation

researcharxiv-cs-ro

Shallow to Deep: Aligning Token Pruning with Stage-wise Roles in LVLMs

model-releasesarxiv-cs-cv

arXiv:2609.25635v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) incur high computational costs from redundant visual tokens. Although training-free attention-based multi-layer pru

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

applicationsarxiv-cs-lg

Silent Sabotage: Internal State Triggered Backdoor Attacks on LLM-Powered Robotic Systems

arXiv:2609.26184v1 Announce Type: new Abstract: The integration of Large Language Models (LLMs) into robotic control systems is enabling a new generation of autonomous agents capable of complex reason

agentsarxiv-cs-ro

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

applicationsarxiv-cs-ro