Search: “papers”

Benchmarking POS Tagging for the Tajik Language: A Comparative Study of Neural Architectures on the TajPersParallel Corpus

arXiv:2605.04576v1 Announce Type: new Abstract: This paper presents the first benchmark for the task of automatic part-of-speech (POS) tagging for the Tajik language. Despite the existence of multilin

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BenCSSmark: Making the Social Sciences Count in LLM Research

DGX agent

arXiv:2605.04886v1 Announce Type: new Abstract: This position paper argues that the under-representation of social science tasks in contemporary LLM benchmarks limits advances in both LLM evaluation a

model-releasesarxiv-cs-cl

7 May 2026

Deepfake Audio Detection Using Self-supervised Fusion Representations

arXiv:2605.03420v1 Announce Type: cross Abstract: This paper describes a submission to the Environment-Aware Speech and Sound Deepfake Detection Challenge (ESDD2) 2026, which addresses component-level

Dr-PoGO: Direct Radar Pose-Graph Optimization

arXiv:2605.04806v1 Announce Type: new Abstract: This paper introduces Dr-PoGO, a method for Simultaneous Localization And Mapping (SLAM) using a 2D spinning radar. Unlike cameras or lidars that requir

applicationsarxiv-cs-ro

Exploring Clustering Capability of Inpainting Model Embeddings for Pattern-based Individual Identification

arXiv:2605.04904v1 Announce Type: new Abstract: In this paper, we explore deep learning techniques for individual identification of animals based on their skin patterns. Individual identification is c

applicationsarxiv-cs-cv

Feature importance analysis for patient management decisions

arXiv:2605.04666v1 Announce Type: new Abstract: The objective of this paper is to understand what characteristics and features of clinical data influence physician's decision about ordering laboratory

Frontier Lag: A Bibliometric Audit of Capability Misrepresentation in Academic AI Evaluation

arXiv:2605.04135v1 Announce Type: cross Abstract: Readers of applied-domain LLM capability evaluations want to know what AI systems can currently do. That literature answers a related, but consequenti

Human-AI Co-Mentorship in Project-Based Learning: A Case Study in Financial Forecasting

arXiv:2605.05144v1 Announce Type: new Abstract: This paper reflects on a AI research project carried out by a team of high-school and early-undergraduate students under the mentorship of graduate rese

applicationsarxiv-cs-lg

ICPR 2026 Competition on Privacy-Preserving Person Re-Identification from Top-View RGB-Depth Camera (TVRID)

model-releasesarxiv-cs-cv

arXiv:2605.04977v1 Announce Type: new Abstract: This companion paper reports the ICPR 2026 TVRID competition on privacy-aware top-view person re-identification. We present the competition setting, the

I'm really excited about this as a new tool in our interpretability tool kit

I'm really excited about this as a new tool in our interpretability tool kit In a new paper, we present NLAs, an unsupervised method for converting an LLM's internal state into human-readable text. I'

safetyjan-leike--x

Intelligent Knowledge Mining Framework: Bridging AI Analysis and Trustworthy Preservation

arXiv:2512.17795v2 Announce Type: replace-cross Abstract: The unprecedented proliferation of digital data presents significant challenges in access, integration, and value creation across all data-int

Learning Time-Varying Graphs from Incomplete Graph Signals

arXiv:2510.17903v3 Announce Type: replace-cross Abstract: This paper tackles the challenging problem of jointly inferring time-varying network topologies and imputing missing data from partially obser

LoViF 2026 The First Challenge on Holistic Quality Assessment for 4D World Model (PhyScore)

model-releasesarxiv-cs-cv

arXiv:2605.05187v1 Announce Type: new Abstract: This paper reports on the LoViF 2026 PhyScore challenge, a competition on holistic quality assessment of world-model-generated videos across both 2D and

Magic-Informed Quantum Architecture Search

model-releasesarxiv-cs-ai

arXiv:2605.03932v1 Announce Type: cross Abstract: Nonstabilizerness, commonly referred to as magic, is a fundamental resource underpinning quantum advantage. In this paper, we propose a magic-informed

Agents

Multi-Agent Strategic Games with LLMs

arXiv:2605.03604v1 Announce Type: cross Abstract: This paper asks whether large language models (LLMs) can be used to study the strategic foundations of conflict and cooperation. I introduce LLMs as e

agentsarxiv-cs-ai

POMA-3D: The Point Map Way to 3D Scene Understanding

arXiv:2511.16567v3 Announce Type: replace Abstract: In this paper, we introduce POMA-3D, the first self-supervised 3D representation model learned from point maps. Point maps encode explicit 3D coordi

safetyarxiv-cs-cv

Right Model, Right Time: Real-Time Cascaded-Fidelity MPC for Bipedal Walking

arXiv:2605.04607v1 Announce Type: new Abstract: This paper presents a multi-phase whole-body model predictive control approach for bipedal walking, combining a detailed whole-body model in the near ho

researcharxiv-cs-ro

Shape2Animal: Creative Animal Generation from Natural Silhouettes

arXiv:2506.20616v3 Announce Type: replace Abstract: Humans possess a unique ability to perceive meaningful patterns in ambiguous stimuli, a cognitive phenomenon known as pareidolia. This paper introdu

applicationsarxiv-cs-cv

Simultaneous CNN Approximation on Manifolds with Applications to Boundary Value Problems

arXiv:2605.04126v1 Announce Type: new Abstract: This paper develops convolutional neural network (CNN) methods for simultaneous approximation and elliptic boundary value problems on compact Riemannian

Local Ai

Structured Progressive Knowledge Activation for LLM-Driven Neural Architecture Search

arXiv:2605.04057v1 Announce Type: new Abstract: This paper focuses on a key challenge in Neural Architecture Search (NAS): integrating established architectural knowledge while exploring new designs u

local-aiarxiv-cs-lg

UFAL-CUNI at SemEval-2026 Task 11: An Efficient Modular Neuro-symbolic Method for Syllogistic Reasoning

arXiv:2605.04941v1 Announce Type: new Abstract: This paper describes our system submitted to SemEval-2026 Task 11: Disentangling Content and Formal Reasoning in Large Language Models. We present an ef

Agents

Agentic AI Systems Should Be Designed as Marginal Token Allocators

arXiv:2605.01214v1 Announce Type: new Abstract: This position paper argues that agentic AI systems should be designed and evaluated as marginal token allocation economies rather than as text generator

agentsarxiv-cs-ai

AI Safety as Control of Irreversibility: A Systems Framework for Decision-Energy and Sovereignty Boundaries

model-releasesarxiv-cs-ai

arXiv:2605.01415v1 Announce Type: new Abstract: Recent AI systems compress the distance between capability growth and capability deployment. Earlier high-risk technologies were slowed by capital inten

AIs and Humans with Agency

arXiv:2605.02810v1 Announce Type: new Abstract: This paper compares agency in humans with potential agency in AI programs. Human agency takes many years to develop, as the frontal lobe is activated. E

applicationsarxiv-cs-ai

Are we Doomed to an AI Race? Why Self-Interest Could Drive Countries Towards a Moratorium on Superintelligence

arXiv:2605.01297v1 Announce Type: cross Abstract: This paper uses game theory to argue that, contrary to the prevailing view, a moratorium on Artificial Superintelligence (ASI) can be in a state's sel

Benchmarking Parameter-Efficient Fine-Tuning of Large Language Models for Low-Resource Tajik Text Generation with the Tajik Web Corpus

arXiv:2605.03742v1 Announce Type: new Abstract: This paper is devoted to the adaptation of generative large language models for the Tajik language, a low-resource language with Cyrillic script. To ove

Local Ai

BIT.UA-AAUBS at ArchEHR-QA 2026: Evaluating Open-Source and Proprietary LLMs via Prompting in Low-Resource QA

arXiv:2605.03618v1 Announce Type: new Abstract: This paper presents the joint participation of the BIT.UA and AAUBS groups in the ArchEHR-QA 2026 shared task, which focuses on clinical question answer

local-aiarxiv-cs-cl

Tutorials

Cripping AI: Reimagining AI Through Lived Disability Experiences

arXiv:2605.02080v1 Announce Type: cross Abstract: Drawing on crip theory, this paper proposes cripping AI as a guiding framework to center lived disability experiences in AI research and development.

tutorialsarxiv-cs-ai

From Data Lifting to Continuous Risk Estimation: A Process-Aware Pipeline for Predictive Monitoring of Clinical Pathways

arXiv:2605.03895v1 Announce Type: new Abstract: This paper presents a reproducible and process-aware pipeline for predictive monitoring of clinical pathways. The approach integrates data lifting, temp

applicationsarxiv-cs-lg

Generative-AI and the transformation of workforce. A job postings-driven analysis

arXiv:2605.00843v1 Announce Type: cross Abstract: This paper investigates how generative-artificial intelligence AI is reshaping job requirements, skill compositions and sectoral dynamics across globa

Height Control and Optimal Torque Planning for Jumping With Wheeled-Bipedal Robots

arXiv:2605.03302v1 Announce Type: new Abstract: This paper mainly studies the accurate height jumping control of wheeled-bipedal robots based on torque planning and energy consumption optimization. Du

safetyarxiv-cs-ro

LLMs Should Not Yet Be Credited with Decision Explanation

arXiv:2605.01164v1 Announce Type: new Abstract: This position paper argues that LLMs should not yet be credited with decision explanation. This matters because recent work increasingly treats accurate

Agents

NaviGNN: Multi-Agent Reinforcement Learning and Graph Neural Network for Sustainable Mobility in Futuristic Smart Cities

arXiv:2507.15143v3 Announce Type: replace Abstract: This paper investigates the feasibility of human mobility in extreme urban morphologies characterized by high-density vertical structures and linear

agentsarxiv-cs-ai

Optimizing Grasping in Legged Robots: A Deep Learning Approach to Loco-Manipulation

arXiv:2508.17466v3 Announce Type: replace-cross Abstract: This paper presents a deep learning framework designed to enhance the grasping capabilities of quadrupeds equipped with arms, with a focus on

researcharxiv-cs-cv

ORPilot: A Production-Oriented Agentic LLM-for-OR Tool for Optimization Modeling

model-releasesarxiv-cs-ai

arXiv:2605.02728v1 Announce Type: new Abstract: This paper presents ORPilot, an open-source agentic AI system that translates real-world business problems into solver-ready optimization models. Unlike

Population-Aware Imitation Learning in Mean-field Games with Common Noise

arXiv:2605.03357v1 Announce Type: new Abstract: Mean Field Games (MFGs) provide a powerful framework for modeling the collective behavior of large populations of interacting agents. In this paper, we

safetyarxiv-cs-lg

Pose Tracking with a Foundation Pose Model and an Ensemble Directional Kalman Filter

arXiv:2605.03105v1 Announce Type: new Abstract: This paper introduces the ensemble directional Kalman filter (EnDKF), an ensemble-based Kalman filtering approach for pose tracking that jointly estimat

Position: LLM Serving Needs Mathematical Optimization and Algorithmic Foundations, Not Just Heuristics

arXiv:2605.01280v1 Announce Type: cross Abstract: This position paper argues that LLM inference serving has outgrown generic heuristics and now demands mathematical optimization and algorithmic founda

Reinforcement Learning Trained Observer Control for Bearings-Only Tracking

arXiv:2605.02120v1 Announce Type: new Abstract: This paper develops a deep reinforcement learning based observer control policy for autonomous bearings-only tracking of a moving target. The observer m

safetyarxiv-cs-ai

Hardware

Robust Visual SLAM for UAV Navigation in GPS-Denied and Degraded Environments: A Multi-Paradigm Evaluation and Deployment Study

arXiv:2605.03678v1 Announce Type: new Abstract: Reliable localization in GPS-denied, visually degraded environments is critical for autonomous UAV opera- tions. This paper presents a systematic compar

hardwarearxiv-cs-ro

Spectral- and Energy-efficient Multi-BS Multi-RIS Pinching-antenna Systems: A GNN-based Approach

arXiv:2605.01307v1 Announce Type: cross Abstract: This paper investigates coordinated downlink transmission in a multi-base station (multi-BS) multi-reconfigurable intelligent surface (multi-RIS)-assi

Structural Ranking of the Cognitive Plausibility of Computational Models of Analogy and Metaphors with the Minimal Cognitive Grid

arXiv:2605.01359v1 Announce Type: new Abstract: In this paper, we employ the Minimal Cognitive Grid (MCG), a framework created to evaluate the cognitive plausibility of artificial systems, to offer a

To Vibe Research or Not to Vibe Research? Generative AI in Qualitative Research

arXiv:2605.00922v1 Announce Type: cross Abstract: There has been intense debate among qualitative researchers about whether generative AI is suitable for qualitative research. In this paper, we summar

Local Ai

Unsupervised Monocular Road Segmentation for Autonomous Driving via Scene Geometry

arXiv:2510.16790v2 Announce Type: replace Abstract: This paper presents a fully unsupervised approach for binary road segmentation (road vs. non-road), eliminating the reliance on costly manually labe

local-aiarxiv-cs-cv

A Systematic Benchmark of Machine Transliteration Models for the Tajik-Farsi Language Pair: A Comparative Study from Rule-Based to Transformer Architectures

arXiv:2605.02270v1 Announce Type: new Abstract: This paper presents the first comprehensive comparative analysis of modern machine learning architectures for transliteration between Tajik (Cyrillic sc

Tutorials

Adaptation of AI-accelerated CFD Simulations to the IPU platform

arXiv:2605.00462v1 Announce Type: cross Abstract: Intelligence Processing Units (IPU) have proven useful for many AI applications. In this paper, we evaluate them within the emerging field of AI for s

tutorialsarxiv-cs-ai

Application Research of a Deep Learning Model Integrating CycleGAN and YOLO in PCB Infrared Defect Detection

arXiv:2601.00237v2 Announce Type: replace Abstract: This paper addresses the critical bottleneck of infrared (IR) data scarcity in Printed Circuit Board (PCB) defect detection by proposing a cross-mod

researcharxiv-cs-cv

CEZSAR: A Contrastive Embedding Method for Zero-Shot Action Recognition

model-releasesarxiv-cs-cv

arXiv:2605.01165v1 Announce Type: new Abstract: This paper proposes a novel Zero-Shot Action Recognition~(ZSAR) method based on contrastive learning. In ZSAR, we aim to classify examples from classes