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A Rigorous, Tractable Measure of Model Complexity

arXiv:2605.21167v1 Announce Type: cross Abstract: An accurate assessment of a model's complexity is crucial for topics such as interpretation, generalization, and model selection. However, most existi

A Semantic and Occlusion-Aware GM-PHD Filter

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Human DGX agent

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arXiv:2605.20666v1 Announce Type: new Abstract: This paper proposes a new birth model including semantic information derived from deep learning to create an occlusion-aware Gaussian Mixture Probabilit

agentsarxiv-cs-ro

21 May 2026

A Sharper Picture of Generalization in Transformers

arXiv:2605.20988v1 Announce Type: new Abstract: We study transformers' generalization behavior on boolean domains from the perspective of the Fourier Spectra of their target functions. In contrast to

A strongly annotated passive acoustic dataset for tropical bird monitoring

arXiv:2605.20578v1 Announce Type: cross Abstract: Passive acoustic monitoring enables continuous, non-invasive biodiversity assessment across diverse ecosystems. The scale of these datasets has driven

A Systematic Comparison between Extractive Self-Explanations and Human Rationales in Text Classification

arXiv:2410.03296v4 Announce Type: replace Abstract: Instruction-tuned LLMs are able to provide extit{an} explanation about their output to users by generating self-explanations, without requiring the

safetyarxiv-cs-cl

A Terrain-Adaptive epsilon-Constraint MPC for Uneven Terrain Kinodynamic Planning

arXiv:2605.21188v1 Announce Type: new Abstract: Kinodynamic planning for car-like vehicles on uneven terrain requires simultaneously optimizing competing objectives such as path efficiency and pose st

researcharxiv-cs-ro

A Typed Tensor Language for Federated Learning

arXiv:2605.21103v1 Announce Type: new Abstract: Federated learning and analytics are often described as collections of separate protocols, even when they share the same mathematical form: client-local

A Unified Framework for Uncertainty-Aware Explainable Artificial Intelligence: A Case Study in Power Quality Disturbance Classification

arXiv:2605.21114v1 Announce Type: new Abstract: Post-hoc explainable AI (XAI) methods typically produce deterministic attribution maps, whereas Bayesian neural networks (BNNs) induce a distribution ov

Hardware

Accelerating Video Inverse Problem Solvers with Autoregressive Diffusion Models

arXiv:2605.20624v1 Announce Type: new Abstract: Diffusion models provide powerful priors for zero-shot video inverse problems, but their real-time deployment is hindered by two inefficiencies: high in

hardwarearxiv-cs-cv

ACL-Verbatim: hallucination-free question answering for research

arXiv:2605.21102v1 Announce Type: new Abstract: Academic researchers need efficient and reliable methods for collecting high-quality information from trusted sources, but modern tools for AI-assisted

Activation-Free Backbones for Image Recognition: Polynomial Alternatives within MetaFormer-Style Vision Models

arXiv:2605.20839v1 Announce Type: new Abstract: Modern vision backbones treat pointwise activations (e.g., ReLU, GELU) and exponential softmax as essential sources of nonlinearity, but we demonstrate

researcharxiv-cs-cv

Ada2MS: A Hybrid Optimization Algorithm Based on Exponential Mixing of Elementwise and Global Second-Moment Estimates

arXiv:2605.20533v1 Announce Type: new Abstract: Optimization algorithms are core methods by which machine learning models iteratively minimize loss functions, update parameters, learn from data, and i

Applications

Adaptive Human-Robot Collaboration for Masonry Construction Under Material and Assembly Uncertainty

arXiv:2605.20264v1 Announce Type: new Abstract: Human-robot collaboration in construction is often challenged by limited robot-to-human communication and the need to adapt to tolerance accumulation ar

applicationsarxiv-cs-ro

Tutorials

Adaptive Probe-based Steering for Robust LLM Jailbreaking

arXiv:2605.20286v1 Announce Type: cross Abstract: Recent work has demonstrated the potential of contrastive steering for jailbreaking Large Language Models (LLMs). However, existing methods rely on li

tutorialsarxiv-cs-lg

Adaptive Signal Resuscitation: Channel-wise Post-Pruning Repair for Sparse Vision Networks

arXiv:2605.21426v1 Announce Type: new Abstract: One-shot magnitude pruning can cause severe accuracy collapse in the high-sparsity regime, even when the pruning mask preserves the largest weights. We

Advanced Scientific Methodology Plays Rossini

arXiv:2605.20220v1 Announce Type: cross Abstract: A musical score provides the essential instructions for its performance while containing indications - at times implicit - regarding the composer's in

Advantage Collapse in Group Relative Policy Optimization: Diagnosis and Mitigation

arXiv:2605.21125v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO), a prominent algorithm within the Reinforcement Learning from Verifiable Rewards (RLVR) framework, has achieve

safetyarxiv-cs-lg

Adversarial Robustness in One-Stage Learning-to-Defer

arXiv:2510.10988v2 Announce Type: replace-cross Abstract: Learning-to-Defer (L2D) enables hybrid decision-making by routing inputs either to a predictor or to external experts. While promising, L2D is

AFD-INSTRUCTION: A Comprehensive Antibody Instruction Dataset with Functional Annotations for LLM-Based Understanding and Design

arXiv:2602.04916v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have significantly advanced protein representation learning. However, their capacity to interpret and design anti

safetyarxiv-cs-cl

Agent JIT Compilation for Latency-Optimizing Web Agent Planning and Scheduling

arXiv:2605.21470v1 Announce Type: new Abstract: Computer-use agents (CUA) automate tasks specified with natural language such as 'order the cheapest item from Taco Bell' by generating sequences of cal

agentsarxiv-cs-lg

AgentAtlas: Beyond Outcome Leaderboards for LLM Agents

arXiv:2605.20530v1 Announce Type: cross Abstract: Large language model agents now act on codebases, browsers, operating systems, calendars, files, and tool ecosystems, but the benchmarks used to evalu

Agentic Physical AI toward a Domain-Specific Foundation Model for Nuclear Reactor Control

arXiv:2512.23292v3 Announce Type: replace-cross Abstract: The prevailing paradigm in AI for physical systems (scaling general-purpose foundation models toward universal multimodal reasoning) confronts

AGPO: Adaptive Group Policy Optimization with Dual Statistical Feedback

arXiv:2605.20722v1 Announce Type: new Abstract: Reinforcement learning improves LLM reasoning, but PPO/GRPO typically use fixed clipping and decoding temperature, which makes training brittle and tuni

AI-Assisted Competency Assessment from Egocentric Video in Simulation-Based Nursing Education

arXiv:2605.20233v1 Announce Type: new Abstract: Assessing learner competency in clinical simulation requires expert observation that is time-intensive, difficult to scale, and subject to inter-rater v

safetyarxiv-cs-cv

AI-Assisted Scientific Assessment: A Case Study on Climate Change

arXiv:2602.09723v2 Announce Type: replace Abstract: The emerging paradigm of AI co-scientists focuses on tasks characterized by repeatable verification, where agents explore search spaces in 'guess an

AI-Augmented Surveys: Leveraging Large Language Models and Surveys for Opinion Prediction

arXiv:2305.09620v4 Announce Type: replace Abstract: Nationally representative surveys track public opinion, yet they ask only a limited set of questions each year, limiting its potential to capture hi

researcharxiv-cs-cl

AI-based Prediction of Independent Construction Safety Outcomes from Universal Attributes

arXiv:1908.05972v3 Announce Type: replace Abstract: This paper significantly improves on, and finishes to validate, an approach proposed in previous research in which safety outcomes were predicted fr

safetyarxiv-cs-lg

AI-Powered Facial Mask Removal Is Not Suitable For Identification

arXiv:2603.27747v2 Announce Type: replace Abstract: Recently, crowd-sourced online criminal investigations have used generative-AI to enhance low-quality visual evidence. In one high-profile case, soc

agentsarxiv-cs-cv

Local Ai

AIGaitor: Privacy-preserving and cloud-free motion analysis for everyone, using edge computing

arXiv:2605.21421v1 Announce Type: new Abstract: Motion capture is the gold standard for measuring human movement, but clinical use remains limited by cost, technical complexity, and privacy concerns.

local-aiarxiv-cs-cv

AIMBio-Mat: An AI-Native FAIR Platform for Closed-Loop Materials Discovery and Biomedical Translation

arXiv:2605.21083v1 Announce Type: cross Abstract: Materials discovery and biomedical translation increasingly require models that can reason across composition, processing, structure, biological respo

safetyarxiv-cs-lg

AIR: Amortized Image Reconstruction Framework for Self-Supervised Feed-Forward 2D Gaussian Splatting

arXiv:2605.20820v1 Announce Type: new Abstract: 2D Gaussian splatting provides an efficient explicit representation for image reconstruction, but existing methods still require costly per-image iterat

researcharxiv-cs-cv

AiraXiv: An AI-Driven Open-Access Platform for Human and AI Scientists

arXiv:2605.21481v1 Announce Type: cross Abstract: Recent advances in artificial intelligence (AI) have accelerated the growth of both human-authored and AI-generated research outputs, placing increasi

agentsarxiv-cs-cl

AirfoilGen: A valid-by-construction and performance-aware latent diffusion model for airfoil generation

arXiv:2605.20303v1 Announce Type: new Abstract: Airfoil shape design is a fundamental task in aerospace engineering, with a direct impact on flight stability and fuel consumption. Deep learning has re

AMAR: Lightweight Attention-Based Multi-User Activity Recognition from Wi-Fi CSI

arXiv:2605.20649v1 Announce Type: cross Abstract: Wi-Fi-based human activity recognition (HAR) has emerged as a promising approach for contactless sensing, leveraging channel state information (CSI) c

An exponential mechanism based on quadratic approximations for fine-tuning machine learning models with privacy guarantees

arXiv:2605.20521v1 Announce Type: new Abstract: Fine-tuning adapts a pretrained machine learning model to a small, sensitive dataset, but this process risks memorizing individual new data points, maki

Anatomy of Agentic Memory: Taxonomy and Empirical Analysis of Evaluation and System Limitations

arXiv:2602.19320v2 Announce Type: replace Abstract: Agentic memory systems enable large language model (LLM) agents to maintain state across long interactions, supporting long-horizon reasoning and pe

AnimeAdapter: Fine-grained and Consistent Zero-shot Anime Character Generation

arXiv:2605.20237v1 Announce Type: new Abstract: We present a lightweight appearance adapter for Stable Diffusion that enables controllable and consistent anime character generation under diverse editi

Anomaly-Informed Confidence Calibration for Vision-Based Safety Prediction

arXiv:2605.21109v1 Announce Type: new Abstract: Reliable confidence estimates are important for safely deploying vision-based controllers in autonomous racing, where safety predictions must be derived

safetyarxiv-cs-ro

Applications

Anti-establishment sentiment on TikTok: Implications for understanding influence(rs) and expertise on social media

arXiv:2508.16453v2 Announce Type: replace-cross Abstract: Distrust of public serving institutions and anti-establishment views are on the rise (especially in the U.S.). As people turn to social media

applicationsarxiv-cs-cl

APEX: Autonomous Policy Exploration for Self-Evolving LLM Agents

arXiv:2605.21240v1 Announce Type: new Abstract: LLM agents have shown strong performance across a wide range of complex tasks, including interactive environments that require long-horizon decision mak

APM: Evaluating Style Personalization in LLMs with Arbitrary Preference Mappings

arXiv:2605.21063v1 Announce Type: new Abstract: Typical LLM responses tend to follow a default style, even though users often have distinct preferences regarding tone, verbosity, and formality that th

Approximation Theory for Neural Networks: Old and New

arXiv:2605.21451v1 Announce Type: new Abstract: Universal approximation theorems provide a mathematical explanation for the expressive power of neural networks. They assert that, under mild conditions

ArchSIBench: Benchmarking the Architectural Spatial Intelligence of Vision-Language Models

arXiv:2605.20837v1 Announce Type: new Abstract: Architectural spatial intelligence, the ability to recognize and infer architectural space, is fundamental to tasks such as robot navigation, embodied i

ArPoMeme: An Annotated Arabic Multimodal Dataset for Political Ideology and Polarization

arXiv:2605.20967v1 Announce Type: new Abstract: Memes have become a prominent medium of political communication in the Arab world, reflecting how humor, imagery, and text interact to express ideologic

researcharxiv-cs-cl

Assessing socio-economic climate impacts from text data

arXiv:2605.20793v1 Announce Type: new Abstract: Recent advances in natural language processing (NLP) and large language models (LLMs) have enabled the systematic use of large-scale textual data from n

researcharxiv-cs-cl

AttriStory: Fine-grained Attribute Realization for Visual Storytelling with Diffusion Models

arXiv:2605.20777v1 Announce Type: new Abstract: Visual storytelling with diffusion models has made impressive strides in maintaining character consistency across narrative scenes. However, a critical

Augmented Analytics and Decision Quality: The Role of Trust among Non-Technical BI Users

arXiv:2605.20198v1 Announce Type: cross Abstract: Augmented analytics has transformed how business intelligence (BI) systems support managerial decision-making. This is especially true for users witho

Auto-Dreamer: Learning Offline Memory Consolidation for Language Agents

arXiv:2605.20616v1 Announce Type: new Abstract: Language agents increasingly operate over streams of related tasks, yet existing memory systems struggle to convert accumulated experience into reusable

agentsarxiv-cs-cl