Search: “papers”

Gaze Authentication: Factors Influencing Authentication Performance

arXiv:2509.10969v3 Announce Type: replace Abstract: This paper examines the key factors that influence the performance of state-of-the-art gaze-based authentication. Experiments were conducted on a la

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Hierarchical Channel Stacking: A Structured Decision Framework for AI-Generated Image Detection

DGX agent

arXiv:2608.26648v1 Announce Type: new Abstract: Many synthetic-image detectors produce accurate predictions but offer limited insight into how those decisions are formed. This paper introduces Hierarc

model-releasesarxiv-cs-cv

28 Aug 2026

Impressive new work from Google DeepMind showing real-world applications of agents for scientific research.

Impressive new work from Google DeepMind showing real-world applications of agents for scientific research. Impressive new paper from Google DeepMind. (bookmark it) It takes Co-Scientist out of simula

applicationsdair-ai--x

Multi-Expert Conformal Risk Control for Pairwise LLM Judging in Open-Ended Dialogue

arXiv:2608.26529v1 Announce Type: new Abstract: In this paper, we explore multi-expert Conformal Risk Control (CRC) algorithms for pairwise LLM-as-a-Judge evaluation in open-ended dialogue. Our core i

Tutorials

The BS-meter: Detecting Politics and Labour through ChatGPT's Language

arXiv:2411.15129v3 Announce Type: replace-cross Abstract: What can we learn about language from studying how it is used by ChatGPT and other large language model (LLM)-based chatbots? In this paper, w

tutorialsarxiv-cs-ai

The Latent Diagnostic Taxonomy: A Framework for Constructing Classifiers and Diagnosing Their Decisions, Applied to Prompt Injection Detection

arXiv:2608.26423v1 Announce Type: cross Abstract: This paper proposes a framework for constructing a classifier as a safeguard layer, and for developing a complementary diagnostic that identifies whic

safetyarxiv-cs-ai

Towards Interpretable Depression Detection: Linking Acoustic Features to DSM-5 Indicators

arXiv:2608.26148v1 Announce Type: new Abstract: Depression affects millions worldwide, yet diagnosis relies on subjective self-reports that may miss authentic behavior. This paper presents an approach

researcharxiv-cs-cl

A Visual Dependence-Aware Framework for Multimodal Unsupervised Continual Post-Training

arXiv:2608.26095v1 Announce Type: new Abstract: In this paper, we explore a novel task of Multimodal Unsupervised Continual Post-Training (MU-CPT), enabling deployed MLLMs to continually evolve from s

safetyarxiv-cs-cv

Advancements in Content-Based Image Retrieval: A Comprehensive Survey of Relevance Feedback Techniques

arXiv:2312.10089v2 Announce Type: replace Abstract: Content-based image retrieval (CBIR) systems have emerged as crucial tools in the field of computer vision, allowing for image search based on visua

How Much Rank Does LoRA Need? Rank-Error Bounds for Transformer Attention

arXiv:2608.26052v1 Announce Type: cross Abstract: Choosing the rank of a low-rank adaptation (LoRA) update is usually an empirical task. In this paper, we provide a task-dependent theory of the approx

researcharxiv-cs-cl

It's a matter of timescale: non-linear utility in successor features and multi-objective planning and learning

arXiv:2608.25723v1 Announce Type: new Abstract: Time is of the essence when dealing with multiple reward signals and non-linear utility. In this paper we argue that the current main approaches in mult

M-Fibration Theory with Applications to Neural Network Compression

arXiv:2608.25598v1 Announce Type: new Abstract: The purpose of this paper is to provide a general, comprehensive, theoretical framework that allows one to deal with fibrations on graphs labelled on a

MoganBert-TR: A Turkish Encoder Foundation Model Trained from Scratch with a CLM-to-MLM Curriculum

arXiv:2608.25768v1 Announce Type: new Abstract: Turkish encoder models have adopted modern architectures while leaving the pretraining objective fixed at masked language modelling. This paper introduc

Performance-guided Task-specific Optimization for Multirotor Design

arXiv:2510.04724v2 Announce Type: replace Abstract: This paper introduces a methodology for task-specific design optimization of multirotor Micro Aerial Vehicles. By leveraging reinforcement learning,

applicationsarxiv-cs-ro

RAEM: Robust Autonomous Exploration for Multi-Floor Environments with a Quadruped Robot

arXiv:2608.25366v1 Announce Type: new Abstract: In this paper, we propose RAEM, a robust autonomous exploration framework for quadruped robots operating in multi-floor environments. Most existing grou

safetyarxiv-cs-ro

Reasoning or Rambling? Exploring the Effect of Thinking on Agent Persuasion

arXiv:2509.21054v2 Announce Type: replace-cross Abstract: Understanding persuasion is critical for the safety and reliability of multi-agent systems built on large language models (LLMs). This paper s

safetyarxiv-cs-cl

VietAIDetector: An Open-Source Zero-Shot Detector for Vietnamese AI-Generated Text

arXiv:2608.25478v1 Announce Type: new Abstract: In recent years, distinguishing between AI-generated text and human-written text has remained a challenge. In this paper, we introduce VietAIDetector, a

researcharxiv-cs-cl

VirTooS: A ROS 2 - Unity Virtualization Toolkit for Fleet Management of Autonomous Mobile Robots

arXiv:2608.26066v1 Announce Type: new Abstract: In this paper, we present VirTooS, a Python/C# toolkit designed to implement fleet-management tasks on teams of Autonomous Mobile Robots (AMRs). VirTooS

agentsarxiv-cs-ro

We’re the Team Behind Apodex 1.1 — Ask Us Anything!

model-releasesr-localllama

Hi r/LocalLLaMA ! We’re Apodex, the team behind Apodex 1.1, our new model family built to scale agentic intelligence for complex work. We’re excited to be here and answer your questions directly. Apod

A Literate Programming Environment for Human and Machine Agents

arXiv:2608.24644v1 Announce Type: cross Abstract: This paper introduces an environment for constructing literate programs in concert with language-aware machine agents. This environment includes a gra

researcharxiv-cs-ai

Adaptive Extrapolated Proximal Gradient Methods with Variance Reduction for Composite Nonconvex Finite-Sum Minimization

arXiv:2502.21099v3 Announce Type: replace-cross Abstract: This paper proposes {sf AEPG-SPIDER}, an Adaptive Extrapolated Proximal Gradient (AEPG) method with variance reduction for minimizing composit

Coronavirus Optimization Algorithm: A Success-History Adaptive Evolutionary Framework with Archive-Assisted Search and Stagnation Recovery for Global Optimization

arXiv:2608.23847v1 Announce Type: cross Abstract: This paper proposes the Coronavirus Optimization Algorithm (COA), a SARS-CoV-2-inspired success-history adaptive evolutionary optimizer for box-constr

Mahalanobis-Based Multi-Head Attention for Complex State Propagation

arXiv:2608.24462v1 Announce Type: new Abstract: In this paper, we propose extbf{Mahalanobis-Based Multi-Head Attention} (MHA-CSP), a novel attention mechanism that replaces the standard dot-product wi

Parameterized Complexity of L_p-Lipschitz Constants for Input Convex Neural Networks and L_p-Norm Maximization over Zonotopes

model-releasesarxiv-cs-lg

arXiv:2608.24865v1 Announce Type: cross Abstract: Lipschitz constants are a standard way to quantify the sensitivity of neural networks to small input perturbations, but computing them is difficult ev

A Survey Instrument to Assess Students' AI and Generative AI Knowledge

arXiv:2608.21391v1 Announce Type: cross Abstract: In this research-to-practice paper we present a survey that can be used to assess students' AI knowledge. As the use of artificial intelligence (AI),

applicationsarxiv-cs-ai

AI-based worker guidance in assembly and disassembly operations using multimodal ego/exo-centric data capture and structured task knowledge

arXiv:2608.22617v1 Announce Type: cross Abstract: Assembly and disassembly processes rely on expert knowledge that is difficult to document, reuse, and transfer. This paper presents a data-centric app

applicationsarxiv-cs-ai

Beyond Verdicts: A Graph-Based Analysis of Human and LLM Reasoning in Scientific Fact-Checking

arXiv:2608.23047v1 Announce Type: cross Abstract: Misinformation that cites legitimate papers can be especially harmful when it distorts what those studies actually report. While existing automatic fa

Closed-loop AI achieves certifiable engineering design

arXiv:2608.21976v1 Announce Type: new Abstract: Agentic AI has automated parts of scientific discovery, including paper generation, expert-level coding, therapeutic proposal, and autonomous experiment

agentsarxiv-cs-ai

Design of a Human-Assistance Robot System with Contextual Action Recognition

arXiv:2608.22028v1 Announce Type: new Abstract: This paper presents a conceptual design for a proactive human assisting robot system capable of recognizing human activities and responding proactively.

researcharxiv-cs-ro

Emotion Intensity Matters: Generating Realistic Expressions in Virtual Humans with CVAEs

arXiv:2608.21697v1 Announce Type: new Abstract: Generating expressive facial behavior in virtual humans (VHs) remains a central challenge in affective computing and character animation. This paper pre

Local Ai

FrugalSOT - Frugal Search Over the Models

arXiv:2608.21621v1 Announce Type: new Abstract: In on-device NLP tasks, limited resources of embedded hardware, such as the Raspberry Pi 5, require efficient inference strategies. This paper introduce

local-aiarxiv-cs-lg

Generative Neural Networks for Sinkhorn Distributionally Robust Hypothesis Testing

arXiv:2608.22746v1 Announce Type: cross Abstract: This paper studies the Sinkhorn distributionally robust hypothesis testing (SDRHT) problem, seeking a robust detector against least-favorable distribu

How Does Research Evolve? Tracing Cross-Domain Trajectories in NLP, ML, and CV Through Claim-Grounded Typed Citations

arXiv:2606.22342v2 Announce Type: replace Abstract: How does research evolve, and can we trace it at the level of individual claims? Scientific progress is not simply a uniform accumulation of facts.

How Useful are LLMs for Grammar Engineering? Cantonese ParGram Resources and Controlled Experimental Evaluation with English Baselines

arXiv:2608.23448v1 Announce Type: new Abstract: This paper presents new Cantonese ParGram resources and evaluates LLMs for knowledge-driven grammar engineering within a controlled experimental paradig

Inertial Manifold Neural Operator for Dissipative Time-Dependent Partial Differential Equations

model-releasesarxiv-cs-lg

arXiv:2608.23546v1 Announce Type: cross Abstract: In this paper, we introduce the Inertial Manifold Neural Operator (IMNO) for solving dissipative time-dependent partial differential equations (PDEs).

Learning Reduced-Order Dynamics with Singularity via Latent-Augmented Neural Ordinary Differential Equations

arXiv:2608.22142v1 Announce Type: new Abstract: This paper addresses the issue of self-intersecting trajectories (in phase space) in industrial reduced-order modeling and proposes the Latent-Augmented

LoViF 2026 The First Challenge on Unified Removal of Raindrops and Reflections: Methods and Results

arXiv:2608.22723v1 Announce Type: new Abstract: This workshop paper comprehensively reviews the First Challenge on Unified Removal of Raindrops and Reflections. The challenge aims to address a frequen

agentsarxiv-cs-cv

Mycelial Search: A Graph-Structured Metaheuristic for Continuous Optimisation

arXiv:2608.23323v1 Announce Type: cross Abstract: Continuous optimisation methods need to balance sharing information and maintaining alternative search directions. In this paper, we introduce Mycelia

Open models, open science. Qwen keeps growing steadily, and we'll always be right here with the research community.🙌 Thanks for the deep di…

Open models, open science. Qwen keeps growing steadily, and we'll always be right here with the research community.🙌 Thanks for the deep dive! @natolambert Over the weekend I had Codex parse 500K arXi

model-releasesqwen--x

Polynomial-Time Mistake-Bounded Language Generation

arXiv:2606.16077v2 Announce Type: replace-cross Abstract: In this paper, we introduce a polynomial-time version of the mistake-bounded language generation (MBLG) framework due to Kleinberg, Peale, and

Power-Performance Characterization of TinyML Systems

arXiv:2608.21646v1 Announce Type: cross Abstract: TinyML systems are enabling machine learning (ML) inference at the edge. However, there is little quantitative analysis of such systems. This paper pr

researcharxiv-cs-ai

Reference-free Human-Object Interaction Editing

model-releasesarxiv-cs-cv

arXiv:2503.09130v2 Announce Type: replace-cross Abstract: This paper presents InteractEdit, a novel framework for reference-free Human-Object Interaction (HOI) editing that tackles the challenging tas

Retrieval-grounded robot program generation and simulation-based correction via Model Context Protocol

arXiv:2608.21417v1 Announce Type: new Abstract: Flexible manufacturing requires industrial robots to be reprogrammed rapidly as product variants change. This paper presents a language-model-based work

Safety-Critical Bilateral Teleoperation for Omnidirectional Aerial Manipulation Using Force-Sensorless Haptic Feedback

arXiv:2608.21735v1 Announce Type: new Abstract: This paper presents a safety-critical bilateral teleoperation framework for omnidirectional aerial manipulators that integrates visual and force-sensorl

safetyarxiv-cs-ro

Semantic Slots for Video Object-Centric Learning

arXiv:2608.21636v1 Announce Type: new Abstract: Video Object-Centric Learning (OCL) has traditionally focused on refining the encoder architecture to ensure temporal consistency. In this paper, we arg

Small Language Model enabled Autonomous agent for Language-Conditioned Cognitive Radar

arXiv:2608.11596v1 Announce Type: cross Abstract: Modern radar systems require adapting their processing strategies in response to changing interference, clutter, and data availability. This paper int

agentsarxiv-cs-ai

The Multilingual FrameNet Corpus

arXiv:2608.23037v1 Announce Type: cross Abstract: This paper introduces the Multilingual FrameNet Corpus (mFNC), a novel resource that extends the English Berkeley FrameNet corpus by collecting and ha

researcharxiv-cs-ai

VibrantLeaves: A principled parametric image generator for training deep restoration models

arXiv:2504.10201v3 Announce Type: replace Abstract: In this paper, we introduce a synthetic image generator relying on a few simple principles, specifically focusing on geometric modeling, textures, a