Search: “papers”

Shared-Roadmap Generation and Evaluator for Multi-Agent Path Planning Using Heterogeneous Graph Neural Network

arXiv:2610.09034v1 Announce Type: cross Abstract: Multi-agent path planning (MAPP) in continuous environments often relies on roadmaps to balance safety and search efficiency. However, traditional roa

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Research

Sharp Asymptotic Theory of Maximum Likelihood Estimation for Gaussian Processes with an RBF Kernel

DGX agent

arXiv:2610.10080v1 Announce Type: cross Abstract: Gaussian processes (GPs) are widely used across machine learning, spatial statistics, time-series analysis, optimization, Bayesian statistics, and sci

researcharxiv-cs-lg

8 Oct 2026

SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning

arXiv:2602.08234v2 Announce Type: replace Abstract: Large Language Model (LLM) agents have shown stunning results in complex tasks, yet they often operate in isolation, failing to learn from past expe

SNR-Gated LSTM-Conditioned Diffusion Model for MIMO Channel Estimation

arXiv:2610.08977v1 Announce Type: new Abstract: Accurate and low latency channel estimation is critical for modern MIMO systems, particularly under mobility, where channels exhibit structured sparsity

Stability and Diversity of Networked Self-Consuming Generative Ecosystems

arXiv:2610.09409v1 Announce Type: new Abstract: The widespread deployment of generative AI has made it increasingly difficult to distinguish synthetic content from real data. Consequently, synthetic d

StableGrasp: Reconstructing Physically Stable Human Hand Grasps from Single Images

arXiv:2610.09195v1 Announce Type: new Abstract: Reconstructing a physically stable human grasp from a single RGB image is challenging because physically modeling grasps is itself difficult, and the pr

Targeted Modality Dropout for Real-Robot Manipulation Robust to Intermittent Vision Loss

arXiv:2610.09566v1 Announce Type: new Abstract: Imitation learning policies that integrate multiple sensory modalities are prone to overreliance on a dominant modality, such as vision, during training

safetyarxiv-cs-ro

Tiny-Scale Chinese BERT Pretraining: A Controlled Comparison of MLM, WWM, and MacBERT Strategies

arXiv:2610.08879v1 Announce Type: new Abstract: Pretraining strategies significantly impact the quality of language models, yet existing comparisons of Masked Language Modeling (MLM), Whole Word Maski

researcharxiv-cs-cl

Towards Calibrated Probabilistic Forecasts for Events of Interest via Outcome-Conditional Recalibration

arXiv:2610.10076v1 Announce Type: cross Abstract: Calibration is an essential requirement for probabilistic predictions to be useful for decision making. While state-of-the-art prediction methods ofte

Two-Level Softmax Sampling Done Right: Correcting Bias from Size Imbalance and Dispersion

arXiv:2610.10483v1 Announce Type: new Abstract: Sampling from a softmax distribution is a fundamental operation in machine learning, but its linear complexity in the number of items makes exact sampli

Unbounded Characteristic and Universal Kernels

arXiv:2610.09731v1 Announce Type: cross Abstract: Kernel methods are among the most powerful tools in machine learning and statistics, with a large number of successful applications. Their immense suc

Unpaired Canonical Correlation Analysis

arXiv:2610.09530v1 Announce Type: cross Abstract: Canonical Correlation Analysis (CCA) is a fundamental method for multiview shared space learning. However, its strict reliance on paired data poses a

WxFM-XL: Adapting Univariate Foundation Models to Multi-Station Weather Forecasting

arXiv:2610.10057v1 Announce Type: new Abstract: With the rise of univariate time series foundation models (e.g., Sundial, Timer), initial efforts have been made to extend them to multivariate settings

Your Prompt Should Do More: Effects of Retrieval Instructions in Embedding Models

arXiv:2610.10508v1 Announce Type: new Abstract: Prompted embedding models have recently received increasing attention, particularly for retrieval, where detailed retrieval instructions are provided as

researcharxiv-cs-cl

Zero-shot Video Moment Retrieval via Off-the-shelf Multimodal Large Language Models

model-releasesarxiv-cs-cv

arXiv:2501.07972v2 Announce Type: replace-cross Abstract: The target of video moment retrieval (VMR) is predicting temporal spans within a video that semantically match a given linguistic query. Exist

A Riemannian Geometry for Low-rank Adaptation

model-releasesarxiv-cs-lg

arXiv:2610.08049v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) is widely used as a parameter-efficient fine-tuning technique for pre-trained deep neural networks, which approximates the we

Agents

A Swarm-Coordinated Multi-Robot System for Early Stress Detection in Agricultural Rows Using Multimodal Leaf Sensing

arXiv:2610.08603v1 Announce Type: cross Abstract: Early stress detection in crops is a necessity today to improve efficiency and reduce waste of time, money, and effort. However, most modern technique

agentsarxiv-cs-ai

Agents

AegisFlow: A Multi-Agent Agentic AI Framework for Autonomous Remediation and Self-Healing in Fragile Data Ecosystems

arXiv:2610.06971v1 Announce Type: new Abstract: Traditional data pipelines are notoriously brittle, often failing due to upstream schema drift, API contract changes, or website DOM modifications. Pres

agentsarxiv-cs-ai

Agentic AI with Structured CoT for Enhancing AI's Spatial Intelligence: Visualization and Reasoning of Rotation

arXiv:2610.04188v2 Announce Type: replace Abstract: Recent studies show that artificial intelligence (AI) with language and vision capabilities still experiences limitations in spatial reasoning. In t

An Empirical Fault Vulnerability Exploration of ReRAM-based Process-in-Memory CNN Accelerators

arXiv:2610.07029v1 Announce Type: cross Abstract: Resistive random-access memory (ReRAM)-based Processing-in-Memory (PIM) accelerator is a promising platform for processing massively memory intensive

An overview of machine learning-enhanced iterative methods for systems of linear and nonlinear equations

arXiv:2610.07211v1 Announce Type: cross Abstract: Systems of equations arise in a wide range of scientific and engineering applications. The present work focuses on solvers for general systems of equa

Anytime-valid simulation-based hypothesis testing

arXiv:2610.08210v1 Announce Type: cross Abstract: For a given data distribution (X_t)_{t in N} sim Q i.i.d., we investigate the hypothesis testing problem: H_0: Q = P_0 vs. H_1: Q = P_1, for two diffe

Ariadne's Thread of LipSync: Unraveling Forgeries via Inconsistency between Lip Motions and Head Poses

arXiv:2610.08417v1 Announce Type: new Abstract: Recent advances in LipSync generation technology have led to the creation of highly realistic videos, posing severe societal risks. However, existing de

Local Ai

Attention from Above: A Multimodal Model for Drone-Based Object Localization

arXiv:2607.17669v2 Announce Type: replace Abstract: Drone-based object detection technology has advanced rapidly, becoming increasingly sophisticated and efficient. Recently, research trends have expa

local-aiarxiv-cs-cv

Benchmarking Time Series Foundation Models for Load Forecasting Under Covariate Uncertainty

model-releasesarxiv-cs-lg

arXiv:2610.07232v1 Announce Type: new Abstract: Accurate short-term load forecasting (STLF) is essential for the reliable and efficient operation of modern power systems. While time series foundation

Beyond Perturbation Magnitude: Direction-Dependent Responses in Multimodal Geometric Representations

arXiv:2610.08533v1 Announce Type: new Abstract: Geometric alignment scores based on Gram determinants provide a compact way to model higher-order consistency among modalities, yet how such scores resp

safetyarxiv-cs-cv

Beyond Refusal Patterns: Safe-Role Internalization for Robust and Generalizable LLM Safety Alignment

arXiv:2610.07023v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved remarkable capabilities but remain vulnerable to jailbreak attacks that elicit harmful or unsafe outputs. Exi

safetyarxiv-cs-ai

Agents

Catching Developers in the Flow: Low-Latency Agentic Program Repair at Google Scale

arXiv:2610.07289v1 Announce Type: cross Abstract: Manual repair of program failures is time-consuming and disruptive for software developers, particularly during the pre-submit phase where test failur

agentsarxiv-cs-ai

Local Ai

CausalBind: Causal Modeling and Learning for Protein-Molecule Virtual Screening

arXiv:2610.07340v1 Announce Type: cross Abstract: Protein-molecule virtual screening is increasingly cast as a problem of representation learning in a shared embedding space. Existing methods rely on

local-aiarxiv-cs-ai

Cite What You Explore: Budget-Aware LLM Reasoning over Medical KGs with Verifiable Evidence

arXiv:2610.07739v1 Announce Type: new Abstract: Post-discharge risk prediction from electronic health records (EHRs) is difficult because many dependencies that link discharge-time observations to dow

Compositional Concept Erasure in Text-to-Image Diffusion Models via Hierarchically Grounded Semantic Surgery

arXiv:2610.07337v1 Announce Type: new Abstract: Removing copyrighted, unsafe, or user-specified concepts from a deployed text-to-image diffusion model is now a practical requirement. Weight-editing me

Local Ai

Computationally efficient goodness-of-fit tests through kernelized Stein discrepancy

arXiv:2512.20007v3 Announce Type: replace-cross Abstract: Models with intractable normalizing constants are widely used in statistics and machine learning. Assessing the adequacy of such models poses

local-aiarxiv-cs-lg

Convergence of Sharpness-Aware Minimization Algorithms using Increasing Batch Size and Decaying Learning Rate

arXiv:2409.09984v2 Announce Type: replace Abstract: The sharpness-aware minimization (SAM) algorithm and its variants, including gap guided SAM (GSAM), have been successful at improving the generaliza

Data-Driven Personas for Survey Simulation: Insights into Simulation Alignment Across Data-Access Regimes

arXiv:2610.05828v2 Announce Type: replace Abstract: Large language models (LLMs) offer new opportunities for public opinion research by enabling early prediction of survey responses, potentially reduc

safetyarxiv-cs-ai

Applications

Deep Learning Based Illegal Bowling Action Detection

arXiv:2610.07223v1 Announce Type: new Abstract: Cricket, often referred to as the 'gentleman's game,' adheres to a strict rule set for both batsmen and bowlers, where each delivery can significantly i

applicationsarxiv-cs-cv

Deep Time-Series Forecasting in 10 Years: A Survey

arXiv:2603.19899v2 Announce Type: replace-cross Abstract: Autocorrelation is a common property of time-series, where each observation is dependent on its predecessors. In deep time-series forecasting,

Direct Regret Optimization in Bayesian Optimization

arXiv:2507.06529v2 Announce Type: replace Abstract: Bayesian optimization (BO) is a powerful paradigm for optimizing expensive black-box functions. Traditional BO methods typically rely on separate ha

Disentangling Dual Image References in Frequency Aware Diffusion Models for Personalized Generation

arXiv:2610.07684v1 Announce Type: cross Abstract: Personalized image generation aims to synthesize text-driven images conditioned on reference images, while mainly casting the generation as image cust

researcharxiv-cs-ai

Does On-Policy Distillation for Safety Pose Backdoor Risks?

arXiv:2610.07654v1 Announce Type: cross Abstract: On-policy distillation (OPD) has attracted growing attention as an effective way to transfer capabilities from teacher models to student models. Recen

safetyarxiv-cs-ai

EC-RAG: Event Chain Retrieval-Augmented Generation for Long Video Understanding

arXiv:2610.08674v1 Announce Type: new Abstract: Current large video-language models (LVLMs) still face challenges when dealing with long videos, mainly because frames are often processed independently

Tutorials

Educating future engineers about LLMs: A scalable workshop

arXiv:2610.07027v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly integrated into engineering workflows, students require hands-on experience to learn how to collabora

tutorialsarxiv-cs-ro

Enhancing High-order Interaction Awareness in LLM-based Recommender Model

arXiv:2409.19979v4 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated prominent reasoning capabilities in recommendation tasks by transforming them into text-generat

researcharxiv-cs-cl

Evaluating Behavioral Context for Interpretable IAM Policy Risk Scoring in Cloud Environments

model-releasesarxiv-cs-lg

arXiv:2610.07345v1 Announce Type: cross Abstract: IAM policy analysis typically emphasizes the authorization capabilities encoded in a policy, but security analyst review priority may also depend on t

Evaluating Escalation Signals for LLM Routing: Targets, Controls, and Five Ways to Fool Yourself

arXiv:2610.07354v1 Announce Type: new Abstract: Deciding when to escalate a query from a small language model to a larger one requires a cheap signal that predicts, before the large model is called, w

FlowCF: Sparse Counterfactual Explanations for Mixed-Type Tabular Data using Flow Matching

arXiv:2610.08537v1 Announce Type: cross Abstract: In the field of Explainable AI (XAI), counterfactual (CF) explanations interpret a model's decision by suggesting the changes to the input that would

Fluorescence-enhanced Whisker Array with Vision-based Deformation Analysis for Underwater Source Localization

arXiv:2610.07275v1 Announce Type: new Abstract: Deep-water biological observation is essential for understanding marine organisms and their interactions with the environment. However, conventional opt

safetyarxiv-cs-ro

GAMEGO: Training Game-Dev Agents with Synthetic Trajectories Anchored in Real-World Assets

arXiv:2610.06910v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have demonstrated remarkable capabilities in web front-end execution, with browser-based game generation

Tutorials

How Learning Governs Unlearning across the Memorization-Generalization Spectrum

arXiv:2610.08577v1 Announce Type: cross Abstract: While unlearning seeks to negate undesired capabilities acquired through learning, little research has examined how the way models learn shapes their

tutorialsarxiv-cs-ai