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ARGUS: Policy-Adaptive Ad Governance via Evolving Reinforcement with Adversarial Umpiring

arXiv:2605.02200v1 Announce Type: new Abstract: Online advertising governance faces significant challenges due to the non-stationary nature of regulatory policies, where emerging mandates (e.g., restr

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ARIS: Agentic and Relationship Intelligence System for Social Robots

DGX agent

arXiv:2605.00943v1 Announce Type: new Abstract: Foundational models have advanced social robotics, enabling richer perception and communicative interaction with users. However, current systems still s

model-releasesarxiv-cs-ro

5 May 2026

Arithmetic in the Wild: Llama uses Base-10 Addition to Reason About Cyclic Concepts

arXiv:2605.01148v1 Announce Type: cross Abstract: Does structure in representations imply structure in computation? We study how Llama-3.1-8B reasons over cyclic concepts (e.g., 'what month is six mon

ARMOR 2025: A Military-Aligned Benchmark for Evaluating Large Language Model Safety Beyond Civilian Contexts

model-releasesarxiv-cs-ai

arXiv:2605.00245v1 Announce Type: new Abstract: Large language models (LLMs) are now being explored for defense applications that require reliable and legally compliant decision support. They also hol

Artificial intelligence language technologies in multilingual healthcare: Grand challenges ahead

arXiv:2605.01441v1 Announce Type: new Abstract: AI language technologies (AILTs), increasingly enabled by large language models (LLMs), are becoming embedded in multilingual healthcare workflows for t

Assistance Without Interruption: A Benchmark and LLM-based Framework for Non-Intrusive Human-Robot Assistance

model-releasesarxiv-cs-ro

arXiv:2605.01368v1 Announce Type: new Abstract: Human-robot interaction (HRI) has long studied how agents and people coordinate to achieve shared goals. In this work, we formalize and benchmark the no

Tutorials

Asymmetric Invertible Threat: Learning Reversible Privacy Defense for Face Recognition

arXiv:2605.01217v1 Announce Type: new Abstract: Face Recognition systems are widely deployed in real-world applications, but they also raise privacy concerns due to unauthorized collection and misuse

tutorialsarxiv-cs-cv

ATLAS: Adaptive Trading with LLM AgentS Through Dynamic Prompt Optimization and Multi-Agent Coordination

arXiv:2510.15949v4 Announce Type: replace-cross Abstract: Large language models show promise for financial decision-making, yet deploying them as autonomous trading agents raises fundamental challenge

agentsarxiv-cs-ai

ATLAS: Article Tracking, Linking, and Analysis of Swedish Encyclopedias

arXiv:2605.02466v1 Announce Type: new Abstract: The digitization of old encyclopedias represents an important step to improve access to historically structured knowledge. Often, however, this process

ATR-Bench: A Federated Learning Benchmark for Adaptation, Trust, and Reasoning

arXiv:2505.16850v2 Announce Type: replace-cross Abstract: Federated Learning (FL) has emerged as a promising paradigm for collaborative model training while preserving data privacy across decentralize

Attention-Based Neural-Augmented Kalman Filter for Legged Robot State Estimation

arXiv:2601.18569v2 Announce Type: replace-cross Abstract: In this letter, we propose an Attention-Based Neural-Augmented Kalman Filter (AttenNKF) for state estimation in legged robots. Foot slip is a

Attention Is Where You Attack

model-releasesarxiv-cs-ai

arXiv:2605.00236v1 Announce Type: cross Abstract: Safety-aligned large language models rely on RLHF and instruction tuning to refuse harmful requests, yet the internal mechanisms implementing safety b

Attention Sink Forges Native MoE in Attention Layers: Sink-Aware Training to Address Head Collapse

arXiv:2602.01203v2 Announce Type: replace Abstract: Large Language Models (LLMs) often assign disproportionate attention to the first token, a phenomenon known as the attention sink. Several recent ap

Attention Sinks in Massively Multilingual Neural Machine Translation:Discovery, Analysis, and Mitigation

arXiv:2605.01229v1 Announce Type: cross Abstract: Cross-attention patterns in neural machine translation (NMT) are widely used to study how multilingual models align linguistic structure. We report a

AttnRouter: Per-Category Attention Routing for Training-Free Image Editing on MMDiT

model-releasesarxiv-cs-cv

arXiv:2605.01480v1 Announce Type: new Abstract: We study training-free image editing on Qwen-Image-Edit-2511, a 60-block multi-modal diffusion transformer (MMDiT) that concatenates noise and source-im

Applications

Attribution-Guided Pruning for Insight and Control: Circuit Discovery and Targeted Correction in Small-scale LLMs

arXiv:2506.13727v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are widely deployed in real-world applications, yet their internal mechanisms remain difficult to interpret and c

applicationsarxiv-cs-cl

Auditing demographic bias in AI-based emergency police dispatch: a cross-lingual evaluation of eleven large language models

arXiv:2605.01451v1 Announce Type: new Abstract: Large language models (LLMs) are rapidly being integrated into high-stakes public safety systems, including emergency call triage and dispatch decision

AutoFocus: Uncertainty-Aware Active Visual Search for GUI Grounding

arXiv:2605.02630v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have enabled autonomous GUI agents that translate natural language instructions into executable screen coordinates. Howeve

agentsarxiv-cs-cv

Automated In-the-Wild Data Collection for Continual AI Generated Image Detection

arXiv:2605.02567v1 Announce Type: new Abstract: The rapid advancement of generative Artificial Intelligence (AI) has introduced significant challenges for reliable AI-generated image detection. Existi

researcharxiv-cs-cv

Automated Interpretability and Feature Discovery in Language Models with Agents

arXiv:2605.01555v1 Announce Type: new Abstract: We introduce an autonomous multiagent framework for mechanistic interpretability that automates both explaining and finding internal features in large l

Automatic Correction of Writing Anomalies in Hausa Texts

arXiv:2506.03820v2 Announce Type: replace Abstract: Hausa texts are often characterized by writing anomalies, such as incorrect character substitutions and spacing errors, which sometimes hinder natur

Applications

Automatic Reflection Level Classification in Hungarian Student Essays

arXiv:2605.02402v1 Announce Type: new Abstract: Reflective thinking is a key competency in education, but assessing reflective writing remains a time-consuming and subjective task for education expert

applicationsarxiv-cs-cl

Autonomous Drift Learning in Data Streams: A Unified Perspective

arXiv:2605.01295v1 Announce Type: new Abstract: In the pursuit of autonomous learning systems, the foundational assumption of stationarity, the premise that data distributions and model behaviors rema

Autonomous QA Agent: A Retrieval-Augmented Framework for Reliable Selenium Script Generation

arXiv:2601.06034v1 Announce Type: cross Abstract: Software testing is critical in the software development lifecycle, yet translating requirements into executable test scripts remains manual and error

agentsarxiv-cs-lg

Autonomous Reliability Qualification of Ga_2O_3-based Hydrogen and Temperature Sensors via Safe Active Learning

arXiv:2605.00868v1 Announce Type: cross Abstract: We present a Safe Active Learning (SAL) framework for autonomous reliability characterization of rectifying Ga_2O_3-based devices under coupled therma

AutoSpatial: Visual-Language Reasoning for Social Robot Navigation through Efficient Spatial Reasoning Learning

model-releasesarxiv-cs-ro

arXiv:2503.07557v2 Announce Type: replace Abstract: We present a novel method, AutoSpatial, an efficient approach with structured spatial grounding to enhance VLMs' spatial reasoning. By combining min

AVA-Bench: Atomic Visual Ability Benchmark for Vision Foundation Models

model-releasesarxiv-cs-cv

arXiv:2506.09082v5 Announce Type: replace Abstract: The rise of vision foundation models (VFMs) calls for systematic evaluation. A common approach pairs VFMs with large language models (LLMs) as gener

AVI-Edit: Audio-sync Video Instance Editing with Granularity-Aware Mask Refiner

arXiv:2512.10571v4 Announce Type: replace Abstract: Recent advancements in video generation highlight that realistic audio-visual synchronization is crucial for engaging content creation. However, exi

agentsarxiv-cs-cv

BadmintonGRF: A Multimodal Dataset and Benchmark for Markerless Ground Reaction Force Estimation in Badminton

model-releasesarxiv-cs-cv

arXiv:2605.01876v1 Announce Type: new Abstract: Multimodal resources for non-periodic court sports with laboratory-grade sensing remain scarce: few publicly pair instrumented ground reaction force (GR

BadSNN: Backdoor Attacks on Spiking Neural Networks via Adversarial Spiking Neuron

arXiv:2602.07200v2 Announce Type: replace-cross Abstract: Spiking Neural Networks (SNNs) are energy-efficient counterparts of Deep Neural Networks (DNNs) with high biological plausibility, as informat

researcharxiv-cs-ai

Balalaika: Data-Centric, Prosody-Aware Annotation Pipeline for Russian Speech

arXiv:2507.13563v2 Announce Type: replace Abstract: We introduce Balalaika, an open-source, data-centric pipeline for processing audio and producing prosody-aware annotations. It combines semantic VAD

BaldWhisper: Faster Whisper with Head Shearing and Layer Merging

arXiv:2510.08599v2 Announce Type: replace-cross Abstract: Pruning large pre-trained transformers in a data-scarce scenario is challenging, as it often requires massive retraining data to recover perfo

Barren Plateaus as Destructive Interference: A Diagnostic Framework and Implications for Structured Ansatzes

arXiv:2605.01319v1 Announce Type: cross Abstract: Barren plateaus (BPs) are usually described by the exponential suppression of gradient variance, but the mechanism by which gradient signal disappears

Barriers to Counterfactual Credit Attribution for Autoregressive Models

arXiv:2605.01425v1 Announce Type: new Abstract: Generative AI disrupts the practice of giving credit to work that came before. Ideally, a generative model would give credit to any work on which its ou

Bayesian Neural Network Surrogates for Bayesian Optimization of Carbon Capture and Storage Operations

arXiv:2507.21803v2 Announce Type: replace Abstract: Carbon Capture and Storage (CCS) stands as a pivotal technology for fostering a sustainable future. The process, which involves injecting supercriti

Beating the Style Detector: Three Hours of Agentic Research on the AI-Text Arms Race

arXiv:2605.02620v1 Announce Type: new Abstract: Reproducing an empirical NLP study used to take weeks. Given the released data and a modern agentic-research harness, we redo every experiment of a rece

Behavior-Grounded Lane Representation Learning for Multi-Task Traffic Digital Twins

arXiv:2605.01901v1 Announce Type: new Abstract: Traffic digital twins are powerful tools for advanced traffic management, and most systems are built on static geometric representations. However, these

safetyarxiv-cs-cv

Benchmarking LightGBM and BiLSTM for Sentiment Analysis on Indonesian E-Commerce Reviews

arXiv:2605.01322v1 Announce Type: new Abstract: This study presents a comparative analysis between two primary approaches in Natural Language Processing (NLP): Machine Learning (ML) utilizing the PyCa

Benchmarking local Hebbian learning rules for memory storage and prototype extraction

model-releasesarxiv-cs-lg

arXiv:2605.01074v1 Announce Type: cross Abstract: Associative memory or content-addressable memory is an important component function in computer science and information processing, and at the same ti

Benchmarking Retrieval Strategies for Biomedical Retrieval-Augmented Generation: A Controlled Empirical Study

arXiv:2605.02520v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) offers a well-established path to grounding large language model (LLM) outputs in external knowledge, yet the quest

Benchmarking Single-Pose Docking, Consensus Rescoring, and Supervised ML on the LIT-PCBA Library: A Critical Evaluation of DiffDock, AutoDock-GPU, GNINA, and DiffDock-NMDN

model-releasesarxiv-cs-lg

arXiv:2605.01681v1 Announce Type: new Abstract: Virtual screening performance depends heavily on the chosen docking and scoring methods. Recent AI-based tools such as DiffDock and NMDN have reported s

Benchmarking Wireless Representations: High-Dimensional vs. Compressed Embeddings for Efficiency and Robustness

model-releasesarxiv-cs-lg

arXiv:2605.02009v1 Announce Type: cross Abstract: Building on recent advances in representation learning for wireless channels, this work investigates the cost-benefit trade-offs of high-dimensional c

Beyond Crash: Hijacking Your Autonomous Vehicle for Fun and Profit

arXiv:2602.07249v2 Announce Type: replace-cross Abstract: Autonomous Vehicles (AVs), especially vision-based AVs, are rapidly being deployed without human operators. As AVs operate in safety-critical

Beyond ECE: Calibrated Size Ratio, Risk Assessment, and Confidence-Weighted Metrics

arXiv:2605.01796v1 Announce Type: new Abstract: Confidence calibration has been dominated by the Expected Calibration Error (ECE), a linear metric that counts calibration offset equally regardless of

Beyond Known Objects: A Novel Framework for Open-Set Object Detection using Negative-Aware Norm

arXiv:2605.02284v1 Announce Type: new Abstract: Open-Set Object Detection (OSOD) is crucial for autonomous driving, where perception systems must recognize and localize both known and previously unsee

agentsarxiv-cs-cv

Beyond Perceptual Shortcuts: Causal-Inspired Debiasing Optimization for Generalizable Video Reasoning in Lightweight MLLMs

arXiv:2605.01324v1 Announce Type: new Abstract: Although reinforcement learning (RL) has significantly advanced reasoning capabilities in large multimodal language models (MLLMs), its efficacy remains

safetyarxiv-cs-cv

Beyond Perplexity: Character Distribution Signatures and the MDTA Benchmark for AI Text Detection

arXiv:2605.01647v1 Announce Type: new Abstract: Training-free AI text detection methods primarily rely on model log-probabilities, achieving strong performance through approaches like Binoculars and D

Beyond Semantic Relevance: Counterfactual Risk Minimization for Robust Retrieval-Augmented Generation

arXiv:2605.01302v1 Announce Type: new Abstract: Standard Retrieval-Augmented Generation (RAG) systems predominantly rely on semantic relevance as a proxy for utility. However, this assumption collapse