Search: “papers”

NAVER LABS Europe Submission to the Instruction-following 2026 Short Track

arXiv:2607.01960v1 Announce Type: new Abstract: In this paper, we describe NAVER LABS Europe's submission to the instruction-following speech processing short track at IWSLT 2026. We participate again

researcharxiv-cs-cl

PACE: A Proxy for Agentic Capability Evaluation

DGX agent

arXiv:2607.02032v1 Announce Type: new Abstract: Evaluating LLM agents on benchmarks like SWE-Bench and GAIA can be expensive, time-consuming, and requires complex infrastructure. A single evaluation c

model-releasesarxiv-cs-ai

3 Jul 2026

Predictive Conformal Slip Monitoring: An Empirical Evaluation of Rolling Split Conformal Prediction for Pre-Incident Traction Loss Detection

arXiv:2607.02124v1 Announce Type: new Abstract: Conventional traction control architectures intervene only after the adhesion limit of a tire has already been breached. This paper investigates whether

QuadRocket: An Aerial Robotic Testbed for Adaptive Thrust-Vector Control of Rocket-Like Vehicles

arXiv:2607.02474v1 Announce Type: new Abstract: This paper presents QuadRocket, a quadrotor-based rocket prototype that provides a low-cost, low-risk platform for validating advanced thrust-vector con

researcharxiv-cs-ro

Real-Time Visual Intelligence on Low-Cost UAVs: A Modular Approach for Tracking, Scanning, and Navigation

arXiv:2607.02298v1 Announce Type: new Abstract: Autonomous drones are rapidly transforming modern warfare and civil applications alike. This paper presents the development of an integrated intelligent

agentsarxiv-cs-ro

Robust Image Processing Techniques for Construction Environment Monitoring Using Underwater Robots

arXiv:2607.01915v1 Announce Type: cross Abstract: This paper proposes a robust image processing framework for underwater robot-based construction environment monitoring, targeting complex degradations

applicationsarxiv-cs-ro

Tight Lower Bounds for the Multi-Secretary Problem via Bellman Certificates

arXiv:2607.02150v1 Announce Type: cross Abstract: This paper studies additive regret in the multi-secretary problem, defined as the gap between the expected offline prophet reward and the reward of th

safetyarxiv-cs-lg

TUDUM: A Turkish-Thinking Reasoning Pipeline for Qwen3.5-27B

arXiv:2607.01927v1 Announce Type: cross Abstract: This paper presents TUDUM (Turkce Dusunen Uretken Model), a project pipeline for adapting a Qwen-family 27B thinking model toward Turkish reasoning. T

Active Sensing for RIS-Aided Tracking and Power Control: A Hybrid Neuroevolution and Supervised Learning Approach

arXiv:2607.00056v1 Announce Type: cross Abstract: This paper studies energy efficient tracking of power-limited mobile users with the assistance of a Reconfigurable Intelligent Surface (RIS). Since lo

agentsarxiv-cs-ai

AD-MPCC: Adaptive Differentiable Model Predictive Contouring Control for Autonomous Racing

model-releasesarxiv-cs-ro

arXiv:2607.00141v1 Announce Type: new Abstract: This paper presents Adaptive Differentiable Model Predictive Contouring Control (AD-MPCC), a framework for autonomous racing that integrates differentia

Beyond Line of Sight: Hybrid Validation of V2X Collective Perception in Complex Scenarios

arXiv:2607.00874v1 Announce Type: new Abstract: This paper introduces a probabilistic framework and hybrid validation methodology for V2X-enabled Collective Perception (CP) in complex traffic scenario

agentsarxiv-cs-ro

Beyond Pixel Overlap: A Framework for Decomposing Segmentation Evaluation Metrics

arXiv:2607.00886v1 Announce Type: new Abstract: Evaluation metrics are central to binary target segmentation because they determine how progress is measured, compared, and interpreted. In this paper,

researcharxiv-cs-cv

Hardware

GPU-Parallel Linearization Error Bounds for Real-Time Robust Optimal Control of Nonlinear and Neural Network Dynamics

arXiv:2607.01203v1 Announce Type: cross Abstract: This paper studies real-time robust optimal control for uncertain nonlinear systems, where linear time-varying (LTV) approximations make planning trac

hardwarearxiv-cs-ai

LLMs in the Real World: Evaluating 'AI' in Emergency Contexts

arXiv:2607.00019v1 Announce Type: cross Abstract: This paper offers a call to action. We urge our colleagues in the research community to play a greater role in the articulation of our findings to the

applicationsarxiv-cs-ai

PixelEyes: Decoupling Perception and Reasoning for Pinpoint Visual Evidence Seeking

model-releasesarxiv-cs-cv

arXiv:2607.00115v1 Announce Type: new Abstract: This paper explores multi-turn visual reasoning and observes that MLLMs repeatedly fail to localize the target, leading to long, redundant trajectories.

SD-RouteFusion: Ego-Trajectory Prediction with SD-Map Route Conditioning

arXiv:2607.01139v1 Announce Type: new Abstract: This paper presents SD-RouteFusion, a deployable end-to-end ego-trajectory prediction method that fuses a front-facing camera, vehicle kinematics, and a

applicationsarxiv-cs-cv

Semantic-Guided Reading Order Reconstruction in Historical Armenian Newspapers with LLMs

arXiv:2607.00596v1 Announce Type: new Abstract: This paper addresses reading order reconstruction in historical Armenian newspapers, which combine complex layouts with limited language resources. We i

applicationsarxiv-cs-cv

Spectral Geometry and Bosonic-Bloch Probes: Explorations in Quantum Learning

arXiv:2607.00063v1 Announce Type: cross Abstract: This paper studies how spectral geometry emerges in quantum learning models and how it can be diagnosed with physically grounded probes. In graph-regu

Speech Playground: An Interactive Tool for Speech Analysis and Comparison

arXiv:2607.00418v1 Announce Type: new Abstract: This paper presents Speech Playground, an interactive speech visualization and comparison tool. While existing tools such as Praat are excellent, it can

safetyarxiv-cs-cl

Svarna: An Open Corpus Workbench for Modern Greek

model-releasesarxiv-cs-cl

arXiv:2607.00970v1 Announce Type: new Abstract: This paper introduces Svarna, a free, open-source, web-based corpus workbench for modern Greek. Svarna integrates five databases covering various regist

Understanding How Humans Inject Knowledge into Machine Learning Workflows through Visual Analytics

model-releasesarxiv-cs-lg

arXiv:2607.00969v1 Announce Type: cross Abstract: Visual analytics (VA) plays an increasingly important role in supporting machine learning (ML) workflows. In the field of visualization, such approach

A Bayesian Filtering Approach for Learning Lagrangian Dynamics from Noisy Measurements

arXiv:2606.31137v1 Announce Type: new Abstract: This paper proposes a Bayesian filtering-based approach for learning the dynamics of a physical system from partial, noisy measurements. We model the sy

A Modular Vision-Language-Action Robotics Framework for Indoor Environments

arXiv:2606.31144v1 Announce Type: cross Abstract: This paper presents an integrated system for the CMU Vision-Language-Action (VLA) Challenge, designed to enable an autonomous agent to perform complex

agentsarxiv-cs-ai

A Technical Typology of AI Systems in Public Administration

arXiv:2606.31755v1 Announce Type: cross Abstract: Research on artificial intelligence (AI) in the public sector often treats 'AI' as a single category, neglecting technical distinctions between differ

agentsarxiv-cs-ai

Benchmarking Large Language Models on Floating-Point Error Classification

arXiv:2606.31308v1 Announce Type: new Abstract: This paper investigates the capability of Large Language Models (LLMs) to detect and classify floating-point errors statically in software code. We intr

Local Ai

CORTEX: Token-Level Hallucination Detection in RAG via Comparative Internal Representations

arXiv:2606.31033v1 Announce Type: new Abstract: In this paper, we propose CORTEX, a token-level hallucination detection method for Retrieval-Augmented Generation (RAG). In long-form RAG outputs, hallu

local-aiarxiv-cs-cl

Dataset Construction for Training LLM to Learn Analog Circuit Knowledge

arXiv:2508.10409v3 Announce Type: replace-cross Abstract: This paper constructs a textual dataset for training large language models (LLMs) to learn analog circuit knowledge and customizes LLM trainin

Improving path-tracking performance of an articulated tractor-trailer system using a non-linear kinematic model

arXiv:2606.31889v1 Announce Type: new Abstract: This paper presents a novel non-linear mathematical model of an articulated tractor-trailer system that can be used, in combination with receding horizo

researcharxiv-cs-ro

Improving Survey Participation in Low-Literacy Populations Through Value-Sensitive Conversational AI

arXiv:2606.30660v1 Announce Type: cross Abstract: Collecting reliable social data from low-literacy populations remains a persistent challenge, particularly when surveys involve sensitive topics and m

Knowledge Distillation from Large Reasoning Models to Compact Student Models: A Case Study on the John O Bryan Mathematics Competition

arXiv:2606.31048v1 Announce Type: cross Abstract: This paper investigates knowledge distillation from a large reasoning model (DeepSeek-R1) to a compact student model (Qwen2.5-7B). Using historical pr

Multilingual Polarization Detection Using Transformer-Based Models with Class Weighting and Threshold Tuning

arXiv:2606.30857v1 Announce Type: new Abstract: This paper describes our submission to SemEval-2026 Task 9 on detecting multilingual, multicultural, and multievent online polarization. We address all

researcharxiv-cs-cl

Online Generation of Collision-Free Trajectories in Dynamic Environments

arXiv:2603.00759v2 Announce Type: replace Abstract: In this paper, we present an online method for converting an arbitrary geometric path, represented by a sequence of states, and generated by any pla

safetyarxiv-cs-ro

Prompting Robot Teams with Natural Language

arXiv:2509.24575v2 Announce Type: replace-cross Abstract: This paper presents a framework to prompt multi-robot teams with high-level tasks using natural language expressions. Our objective is to use

safetyarxiv-cs-lg

Separation Capacity of Scattering Networks

arXiv:2606.30822v1 Announce Type: cross Abstract: In this paper, we attempt to enhance the theoretical understanding of convolutional neural networks (CNNs) as feature extractors in classification tas

Teaching LLMs String Matching, Backtracking, and Error Recovery to Deduce Bases and Truth Tables for the Combinatorially Exploding Bit Manipulation Puzzles

arXiv:2606.23672v2 Announce Type: replace Abstract: This paper presents our algorithmic innovations for the NVIDIA Nemotron Model Reasoning Challenge, focusing on Bit Manipulation Puzzles. In this tas

Wait, am I Being Fair? Characterizing Deductive Stereotyping and Mitigating It with Fair-GCG

arXiv:2606.30989v1 Announce Type: cross Abstract: Warning: This paper contains several toxic and offensive statements. While reasoning generally improves fairness in recent large language models (LLMs

safetyarxiv-cs-ai

A Posteriori Error Analysis for Decoupled Neural Approximations of Fully Coupled FBSDEs with Control Mismatch

arXiv:2606.29474v1 Announce Type: cross Abstract: This paper develops an a posteriori error analysis framework for decoupled neural approximations of fully coupled forward--backward stochastic differe

Accurate Recognition of Pneumonia and COVID-19 by Geometric Shape Normalization of Lung Region using Automatic Landmark Detection and Piecewise Affine Warping

arXiv:2606.29715v1 Announce Type: new Abstract: This paper presents an automatic system for recognizing pulmonary diseases in chest X-rays using geometric normalization of the lung region. The method

safetyarxiv-cs-cv

Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS

arXiv:2606.29665v1 Announce Type: cross Abstract: This paper examines how metric adjustments to Multidimensional Scaling (MDS) can enhance its effectiveness as a visual tool for pattern recognition. T

AerialMetric: Benchmarking and Adapting UAV Monocular Metric Depth Estimation in the Real World

model-releasesarxiv-cs-cv

arXiv:2606.29716v1 Announce Type: new Abstract: This paper addresses the problem of monocular metric depth estimation in aerial UAV imagery. Although recent data-driven methods have achieved remarkabl

An Agentic AI Pipeline for Appliance-Level Energy Anomaly Detection and LLM-Driven Recommendations

arXiv:2606.28467v1 Announce Type: cross Abstract: Appliance-level energy monitoring in office buildings produces noisy alerts that non-expert facility managers struggle to use. This paper proposes an

An Integrated Two-Stage Deep-Learning Tool for Rapid Post-Hurricane Damage Identification and Repair Scheduling

arXiv:2606.29117v1 Announce Type: cross Abstract: Post-hurricane damage assessment and repair scheduling can require computationally intensive simulation and optimization. This paper presents an integ

Arbitrary Reduction of Validation Error for AI Decision Tests using Homomorphic AI and Repetition Codes

arXiv:2606.28994v1 Announce Type: cross Abstract: This paper presents new results and breakthrough obtained with the HbHAI techniques (Hash-based Homomorphic Artificial Intelligence) proposed in ite{f

ARMOR: Adaptive Retriever Optimization for Low-Resource Telecom Question Answering

arXiv:2606.29706v1 Announce Type: cross Abstract: Telecom question answering (QA) is a challenging setting for retrieval-augmented generation (RAG): evidence is fragmented across standards, papers, en

Attention Enhanced Entity Recommendation for Intelligent Monitoring in Cloud Systems

arXiv:2510.20640v2 Announce Type: replace Abstract: In this paper, we present DiRecGNN, an attention-enhanced entity recommendation framework for monitoring cloud services at Microsoft. We provide ins

applicationsarxiv-cs-lg

Building Multi-Task Agentic LLMs via Two-Phase Distillation

arXiv:2606.30044v1 Announce Type: new Abstract: A key step toward artificial general intelligence is to train models that can perform multiple tasks. In this paper, we study how to build such models b

safetyarxiv-cs-lg

Tutorials

Clustering Unsupervised Representations as Defense against Poisoning Attacks on Speech Commands Classification System

arXiv:2606.28953v1 Announce Type: cross Abstract: Poisoning attacks entail attackers intentionally tampering with training data. In this paper, we consider a dirty-label poisoning attack scenario on a

tutorialsarxiv-cs-ai

Contact-Anchored Proprioceptive Odometry for Legged and Wheel-Legged Robots

arXiv:2602.17393v3 Announce Type: replace Abstract: Reliable odometry for legged robots without cameras or LiDAR remains challenging due to IMU drift and noisy joint velocity sensing. This paper prese

researcharxiv-cs-ro