Search: “papers”

Quantum Non-Linear Bandit Optimization

arXiv:2503.03023v2 Announce Type: replace Abstract: We study non-linear bandit optimization where the learner maximizes a black-box function with zeroth order function oracle, which has been successfu

applicationsarxiv-cs-lg

Quantum spatial best-arm identification via quantum walks

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arXiv:2509.05890v3 Announce Type: replace-cross Abstract: Quantum reinforcement learning has emerged as a framework combining quantum computation with sequential decision-making, and applications to t

researcharxiv-cs-ai

22 Apr 2026

Reasoning Structure Matters for Safety Alignment of Reasoning Models

arXiv:2604.18946v1 Announce Type: new Abstract: Large reasoning models (LRMs) achieve strong performance on complex reasoning tasks but often generate harmful responses to malicious user queries. This

Reduced-Order Surrogates for Forced Flexible Mesh Coastal-Ocean Models

arXiv:2602.05416v2 Announce Type: replace-cross Abstract: While proper orthogonal decomposition (POD)-based surrogates are widely explored for hydrodynamic applications, the use of Koopman autoencoder

applicationsarxiv-cs-ai

Refute-or-Promote: An Adversarial Stage-Gated Multi-Agent Review Methodology for High-Precision LLM-Assisted Defect Discovery

arXiv:2604.19049v1 Announce Type: cross Abstract: LLM-assisted defect discovery has a precision crisis: plausible-but-wrong reports overwhelm maintainers and degrade credibility for real findings. We

agentsarxiv-cs-ai

Reinforcement Learning Enabled Adaptive Multi-Task Control for Bipedal Soccer Robots

arXiv:2604.19104v1 Announce Type: cross Abstract: Developing bipedal football robots in dynamiccombat environments presents challenges related to motionstability and deep coupling of multiple tasks, a

researcharxiv-cs-ai

Tutorials

Relational AI in Education: Reciprocity, Participatory Design, and Indigenous Worldviews

arXiv:2604.19099v1 Announce Type: cross Abstract: Education is not merely the transmission of information or the optimisation of individual performance; it is a fundamentally social, constructive, and

tutorialsarxiv-cs-ai

Rethinking Scale: Deployment Trade-offs of Small Language Models under Agent Paradigms

arXiv:2604.19299v1 Announce Type: cross Abstract: Despite the impressive capabilities of large language models, their substantial computational costs, latency, and privacy risks hinder their widesprea

agentsarxiv-cs-ai

S2MAM: Semi-supervised Meta Additive Model for Robust Estimation and Variable Selection

arXiv:2604.19072v1 Announce Type: cross Abstract: Semi-supervised learning with manifold regularization is a classical framework for jointly learning from both labeled and unlabeled data, where the ke

applicationsarxiv-cs-ai

Scheduling Analysis of UAV Flight Control Workloads using Raspberry Pi 5 Using PREEMPT_RT Linux

arXiv:2604.19275v1 Announce Type: cross Abstract: Modern UAV architectures increasingly aim to unify high-level autonomy and low-level flight control on a single General-Purpose Operating System (GPOS

researcharxiv-cs-ro

Scripts Through Time: A Survey of the Evolving Role of Transliteration in NLP

arXiv:2604.18722v1 Announce Type: new Abstract: Cross-lingual transfer in NLP is often hindered by the ``script barrier'' where differences in writing systems inhibit transfer learning between languag

Separating Geometry from Probability in the Analysis of Generalization

arXiv:2604.19560v1 Announce Type: new Abstract: The goal of machine learning is to find models that minimize prediction error on data that has not yet been seen. Its operational paradigm assumes acces

Sherpa.ai Privacy-Preserving Multi-Party Entity Alignment without Intersection Disclosure for Noisy Identifiers

arXiv:2604.19219v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative model training among multiple parties without centralizing raw data. There are two main paradigms in FL:

SpanVLA: Efficient Action Bridging and Learning from Negative-Recovery Samples for Vision-Language-Action Model

arXiv:2604.19710v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models offer a promising autonomous driving paradigm for leveraging world knowledge and reasoning capabilities, especially

safetyarxiv-cs-cv

Local Ai

Speculative End-Turn Detector for Efficient Speech Chatbot Assistant

arXiv:2503.23439v2 Announce Type: replace-cross Abstract: Spoken dialogue systems powered by large language models have demonstrated remarkable abilities in understanding human speech and generating a

local-aiarxiv-cs-ai

Stable-RAG: Mitigating Retrieval-Permutation-Induced Hallucinations in Retrieval-Augmented Generation

arXiv:2601.02993v4 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) has become a key paradigm for reducing factual hallucinations in Large Language Models (LLMs), yet little is kn

safetyarxiv-cs-cl

STAR-Teaming: A Strategy-Response Multiplex Network Approach to Automated LLM Red Teaming

arXiv:2604.18976v1 Announce Type: new Abstract: While Large Language Models (LLMs) are widely used, they remain susceptible to jailbreak prompts that can elicit harmful or inappropriate responses. Thi

safetyarxiv-cs-cl

StochasTok: Improving Fine-Grained Subword Understanding in LLMs

arXiv:2506.01687v3 Announce Type: replace Abstract: Subword-level understanding is integral to numerous tasks, including understanding multi-digit numbers, spelling mistakes, abbreviations, rhyming, a

Local Ai

StrikeWatch: Wrist-worn Gait Recognition with Compact Time-series Models on Low-power FPGAs

arXiv:2510.24738v2 Announce Type: replace-cross Abstract: Running offers substantial health benefits, but improper gait patterns can lead to injuries, particularly without expert feedback. While prior

local-aiarxiv-cs-lg

Tutorials

TACENR: Task-Agnostic Contrastive Explanations for Node Representations

arXiv:2604.19372v1 Announce Type: cross Abstract: Graph representation learning has achieved notable success in encoding graph-structured data into latent vector spaces, enabling a wide range of downs

tutorialsarxiv-cs-ai

TFusionOcc: T-Primitive Based Object-Centric Multi-Sensor Fusion Framework for 3D Occupancy Prediction

arXiv:2602.06400v2 Announce Type: replace-cross Abstract: The prediction of 3D semantic occupancy enables autonomous vehicles (AVs) to perceive the fine-grained geometric and semantic scene structure

agentsarxiv-cs-ai

The Logical Expressiveness of Topological Neural Networks

arXiv:2604.19212v1 Announce Type: new Abstract: Graph neural networks (GNNs) are the standard for learning on graphs, yet they have limited expressive power, often expressed in terms of the Weisfeiler

Model Releases

The Rise of Verbal Tics in Large Language Models: A Systematic Analysis Across Frontier Models

model-releasesarxiv-cs-ai

arXiv:2604.19139v1 Announce Type: cross Abstract: As Large Language Models (LLMs) continue to evolve through alignment techniques such as Reinforcement Learning from Human Feedback (RLHF) and Constitu

The Triadic Loop: A Framework for Negotiating Alignment in AI Co-hosted Livestreaming

arXiv:2604.18850v1 Announce Type: cross Abstract: AI systems are increasingly embedded in multi-user social environments, yet most alignment frameworks conceptualize interaction as a dyadic relationsh

Towards a Linguistic Evaluation of Narratives: A Quantitative Stylistic Framework

arXiv:2604.19261v1 Announce Type: new Abstract: The evaluation of narrative quality remains a complex challenge, as it involves subjective factors such as plot, character development, and emotional im

TrEEStealer: Stealing Decision Trees via Enclave Side Channels

arXiv:2604.18716v1 Announce Type: cross Abstract: Today, machine learning is widely applied in sensitive, security-related, and financially lucrative applications. Model extraction attacks undermine c

TROJail: Trajectory-Level Optimization for Multi-Turn Large Language Model Jailbreaks with Process Rewards

arXiv:2512.07761v3 Announce Type: replace Abstract: Large language models have seen widespread adoption, yet they remain vulnerable to multi-turn jailbreak attacks, threatening their safe deployment.

Ultrametric OGP - parametric RDT symmetric binary perceptron connection

arXiv:2604.19712v1 Announce Type: new Abstract: In [97,99,100], an fl-RDT framework is introduced to characterize statistical computational gaps (SCGs). Studying symmetric binary perceptrons (SBPs), [

Understanding LLM Performance Degradation in Multi-Instance Processing: The Roles of Instance Count and Context Length

arXiv:2603.22608v2 Announce Type: replace Abstract: Users often rely on Large Language Models (LLMs) for processing multiple documents or performing analysis over a number of instances. For example, a

researcharxiv-cs-ai

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images

arXiv:2604.19257v1 Announce Type: new Abstract: Creating realistic and simulation-ready 3D assets is crucial for autonomous driving research and virtual environment construction. However, existing 3D

agentsarxiv-cs-cv

Vibe coders are not going to like this. UC San Diego just published the first real field study of experienced developers using AI agents. Th…

Vibe coders are not going to like this. UC San Diego just published the first real field study of experienced developers using AI agents. They watched 13 of them code in the wild and surveyed 99 more.

agentsgary-marcus--x

Vision-Based Human Awareness Estimation for Enhanced Safety and Efficiency of AMRs in Industrial Warehouses

arXiv:2604.18627v1 Announce Type: new Abstract: Ensuring human safety is of paramount importance in warehouse environments that feature mixed traffic of human workers and autonomous mobile robots (AMR

safetyarxiv-cs-cv

Visual Adversarial Attack on Vision-Language Models for Autonomous Driving

arXiv:2411.18275v2 Announce Type: replace Abstract: Vision-language models (VLMs) have significantly advanced autonomous driving (AD) by enhancing reasoning capabilities. However, these models remain

safetyarxiv-cs-cv

VoteGCL: Enhancing Graph-based Recommendations with Majority-Voting LLM-Rerank Augmentation

arXiv:2507.21563v4 Announce Type: replace-cross Abstract: Recommendation systems often suffer from data sparsity caused by limited user-item interactions, which degrade their performance and amplify p

safetyarxiv-cs-lg

When Langevin Monte Carlo Meets Randomization: Non-asymptotic Error Bounds beyond Log-Concavity and Gradient Lipschitzness

arXiv:2509.25630v2 Announce Type: replace-cross Abstract: Efficient sampling from complex and high dimensional target distributions turns out to be a fundamental task in diverse disciplines such as sc

Wrench-Aware Admittance Control for Unknown-Payload Manipulation

arXiv:2604.19469v1 Announce Type: new Abstract: Unknown payloads can strongly affect compliant robotic manipulation, especially when the payload center of mass is not aligned with the tool center poin

researcharxiv-cs-ro

A B-Spline Function Based 3D Point Cloud Unwrapping Scheme for 3D Fingerprint Recognition and Identification

arXiv:2604.16546v1 Announce Type: new Abstract: Three-dimensional (3D) fingerprint recognition and identification offer several advantages over traditional two-dimensional (2D) recognition systems. Th

researcharxiv-cs-cv

Model Releases

A Comparative Evaluation of Geometric Accuracy in NeRF and Gaussian Splatting

model-releasesarxiv-cs-cv

arXiv:2604.18205v1 Announce Type: new Abstract: Recent advances in neural rendering have introduced numerous 3D scene representations. Although standard computer vision metrics evaluate the visual qua

A Computational Method for Measuring 'Open Codes' in Qualitative Analysis

arXiv:2411.12142v4 Announce Type: replace Abstract: Qualitative analysis is critical to understanding human datasets in many social science disciplines. A central method in this process is inductive c

A Goal Without a Plan Is Just a Wish: Efficient and Effective Global Planner Training for Long-Horizon Agent Tasks

arXiv:2510.05608v2 Announce Type: replace Abstract: Agents based on large language models (LLMs) struggle with brainless trial-and-error and generating hallucinatory actions due to a lack of global pl

agentsarxiv-cs-cl

A Hamilton-Jacobi Reachability-Guided Search Framework for Efficient and Safe Indoor Planar Robot Navigation

arXiv:2604.17679v1 Announce Type: new Abstract: Autonomous navigation requires planning to reach a goal safely and efficiently in complex and potentially dynamic environments. Graph search-based algor

safetyarxiv-cs-ro

Local Ai

A Lightweight Transformer for Pain Recognition from Brain Activity

arXiv:2604.16491v1 Announce Type: new Abstract: Pain is a multifaceted and widespread phenomenon with substantial clinical and societal burden, making reliable automated assessment a critical objectiv

local-aiarxiv-cs-cv

A Mechanism Study of Delayed Loss Spikes in Batch-Normalized Linear Models

arXiv:2604.16809v1 Announce Type: cross Abstract: Delayed loss spikes have been reported in neural-network training, but existing theory mainly explains earlier non-monotone behavior caused by overly

Model Releases

A Note on TurboQuant and the Earlier DRIVE/EDEN Line of Work

model-releasesarxiv-cs-lg

arXiv:2604.18555v1 Announce Type: new Abstract: This note clarifies the relationship between the recent TurboQuant work and the earlier DRIVE (NeurIPS 2021) and EDEN (ICML 2022) schemes. DRIVE is a 1-

A Rapid Deployment Pipeline for Autonomous Humanoid Grasping Based on Foundation Models

arXiv:2604.17258v1 Announce Type: new Abstract: Deploying a humanoid robot to manipulate a new object has traditionally required one to two days of effort: data collection, manual annotation, 3D model

agentsarxiv-cs-ro

A Unified Compliance Aggregator Framework for Automated Multi-Tool Security Assessment of Linux Systems

arXiv:2604.17256v1 Announce Type: cross Abstract: Assessing the security posture of modern computing systems typically requires the use of multiple specialized tools. These tools focus on different as

Adaptive Quantized Planetary Crater Detection System for Autonomous Space Exploration

arXiv:2508.18025v4 Announce Type: replace-cross Abstract: Autonomous planetary exploration demands real-time, high-fidelity environmental perception. Standard deep learning models require massive comp

agentsarxiv-cs-cv

Adjustment of Cluster-Then-Predict Framework for Multiport Scatterer Load Prediction

arXiv:2602.08129v2 Announce Type: replace-cross Abstract: Predicting interdependent load values in multiport scatterers is challenging due to high dimensionality and complex dependence between impedan

applicationsarxiv-cs-lg