All entries

A Quantitative Definition of Intelligence

arXiv:2604.10873v1 Announce Type: new Abstract: We propose an operational, quantitative definition of intelligence for arbitrary physical systems. The intelligence density of a system is the ratio of

Safety

A Queueing-Theoretic Framework for Dynamic Attack Surfaces: Data-Integrated Risk Analysis and Adaptive Defense

Content type

All Blog X Post Paper YouTube Reddit GitHub

DGX agent

arXiv:2604.10427v1 Announce Type: cross Abstract: We develop a queueing-theoretic framework to model the temporal evolution of cyber-attack surfaces, where the number of active vulnerabilities is repr

safetyarxiv-cs-ai

14 Apr 2026

A Ray Intersection Algorithm for Fast Growth Distance Computation Between Convex Sets

model-releasesarxiv-cs-ro

arXiv:2604.10058v1 Announce Type: new Abstract: In this paper, we discuss an efficient algorithm for computing the growth distance between two compact convex sets with representable support functions.

A robust and adaptive MPC formulation for Gaussian process models

arXiv:2507.02098v2 Announce Type: replace-cross Abstract: In this paper, we present a robust and adaptive model predictive control (MPC) framework for uncertain nonlinear systems affected by bounded d

tutorialsarxiv-cs-lg

A Structured Clustering Approach for Inducing Media Narratives

arXiv:2604.10368v1 Announce Type: new Abstract: Media narratives wield tremendous power in shaping public opinion, yet computational approaches struggle to capture the nuanced storytelling structures

researcharxiv-cs-cl

A Survey of Inductive Reasoning for Large Language Models

arXiv:2510.10182v2 Announce Type: replace-cross Abstract: Reasoning is an important task for large language models (LLMs). Among all the reasoning paradigms, inductive reasoning is one of the fundamen

A Survey on 3D Gaussian Splatting Applications: Segmentation, Editing, and Generation

arXiv:2508.09977v4 Announce Type: replace Abstract: In the context of novel view synthesis, 3D Gaussian Splatting (3DGS) has recently emerged as an efficient and competitive counterpart to Neural Radi

researcharxiv-cs-cv

A Survey on Deep Learning Techniques for Action Anticipation

arXiv:2309.17257v2 Announce Type: replace Abstract: The ability to anticipate possible future human actions is essential for a wide range of applications, including autonomous driving and human-robot

agentsarxiv-cs-cv

A Systematic Analysis of the Impact of Persona Steering on LLM Capabilities

arXiv:2604.11048v1 Announce Type: cross Abstract: Imbuing Large Language Models (LLMs) with specific personas is prevalent for tailoring interaction styles, yet the impact on underlying cognitive capa

A Tale of Two Temperatures: Simple, Efficient, and Diverse Sampling from Diffusion Language Models

arXiv:2604.09921v1 Announce Type: new Abstract: Much work has been done on designing fast and accurate sampling for diffusion language models (dLLMs). However, these efforts have largely focused on th

tutorialsarxiv-cs-lg

A Temporally Augmented Graph Attention Network for Affordance Classification

arXiv:2604.10149v1 Announce Type: cross Abstract: Graph attention networks (GATs) provide one of the best frameworks for learning node representations in relational data; but, existing variants such a

A Triadic Suffix Tokenization Scheme for Numerical Reasoning

arXiv:2604.11582v1 Announce Type: cross Abstract: Standard subword tokenization methods fragment numbers inconsistently, causing large language models (LLMs) to lose positional and decimal structure -

Local Ai

A Two-Stage Dual-Modality Model for Facial Emotional Expression Recognition

arXiv:2603.12221v2 Announce Type: replace Abstract: This paper addresses the expression (EXPR) recognition challenge in the 10th Affective Behavior Analysis in-the-Wild (ABAW) workshop and competition

local-aiarxiv-cs-cv

A Unified Theory of Sparse Dictionary Learning in Mechanistic Interpretability: Piecewise Biconvexity and Spurious Minima

arXiv:2512.05534v4 Announce Type: replace-cross Abstract: As AI models achieve remarkable capabilities across diverse domains, understanding what representations they learn and how they encode concept

A Weak Penalty Neural ODE for Learning Chaotic Dynamics from Noisy Time Series

model-releasesarxiv-cs-lg

arXiv:2511.06609v3 Announce Type: replace Abstract: The accurate forecasting of complex, high-dimensional dynamical systems from observational data is a fundamental task across numerous scientific and

A3-FPN: Asymptotic Content-Aware Pyramid Attention Network for Dense Visual Prediction

arXiv:2604.10210v1 Announce Type: new Abstract: Learning multi-scale representations is the common strategy to tackle object scale variation in dense prediction tasks. Although existing feature pyrami

researcharxiv-cs-cv

Local Ai

Abliterated (uncensored) models

This r/ollama discussion covers 'abliterated' models — LLMs that have had their built-in refusal mechanisms removed through a technique called abliteration, allowing them to respond to prompts without

local-air-ollama

AbLWR:A Context-Aware Listwise Ranking Framework for Antibody-Antigen Binding Affinity Prediction via Positive-Unlabeled Learning

arXiv:2604.11272v1 Announce Type: cross Abstract: Accurate prediction of antibody-antigen binding affinity is fundamental to therapeutic design, yet remains constrained by severe label sparsity and th

Local Ai

ABot-Claw: A Foundation for Persistent, Cooperative, and Self-Evolving Robotic Agents

arXiv:2604.10096v1 Announce Type: new Abstract: Current embodied intelligent systems still face a substantial gap between high-level reasoning and low-level physical execution in open-world environmen

local-aiarxiv-cs-cv

Absorption and Inertness in Coarse-Grained Arithmetic: A Heuristic Application to the St. Petersburg Paradox

arXiv:2507.12475v2 Announce Type: replace-cross Abstract: The St. Petersburg paradox presents a longstanding challenge in decision theory: its classical expected value diverges, yet no correspondingly

AC-MIL: Weakly Supervised Atrial LGE-MRI Quality Assessment via Adversarial Concept Disentanglement

model-releasesarxiv-cs-cv

arXiv:2604.10303v1 Announce Type: new Abstract: High-quality Late Gadolinium Enhancement (LGE) MRI can be helpful for atrial fibrillation management, yet scan quality is frequently compromised by pati

Accelerated Dopant Screening in Oxide Semiconductors via Multi-Fidelity Contextual Bandits and a Three-Tier DFT Validation Funnel

model-releasesarxiv-cs-lg

arXiv:2604.10157v1 Announce Type: cross Abstract: Band gap engineering of oxide semiconductors through doping is critical for photocatalysis and optoelectronics, yet the combinatorial space of dopant

ACCIDENT: A Benchmark Dataset for Vehicle Accident Detection from Traffic Surveillance Videos

arXiv:2604.09819v1 Announce Type: cross Abstract: We introduce ACCIDENT, a benchmark dataset for traffic accident detection in CCTV footage, designed to evaluate models in supervised (IID and OOD) and

AccidentSim: Generating Vehicle Collision Videos with Physically Realistic Collision Trajectories from Real-World Accident Reports

arXiv:2503.20654v4 Announce Type: replace-cross Abstract: Collecting real-world vehicle accident videos for autonomous driving research is challenging due to their rarity and complexity. While existin

agentsarxiv-cs-ai

ACE-Bench: A Lightweight Benchmark for Evaluating Azure SDK Usage Correctness

arXiv:2604.09564v1 Announce Type: cross Abstract: We present ACE-Bench (Azure SDK Coding Evaluation Benchmark), an execution-free benchmark that provides fast, reproducible pass or fail signals for wh

ACE-TA: An Agentic Teaching Assistant for Grounded Q&A, Quiz Generation, and Code Tutoring

arXiv:2604.09572v1 Announce Type: cross Abstract: We introduce ACE-TA, the Agentic Coding and Explanations Teaching Assistant framework, that autonomously routes conceptual queries drawn from programm

agentsarxiv-cs-ai

Achieving Skilled and Reliable Daily Probabilistic Forecasts of Wind Power at Subseasonal-to-Seasonal Timescales over France

arXiv:2511.16164v2 Announce Type: replace Abstract: In a growing renewable based energy system, accurate and reliable wind power forecasts are crucial for grid stability, balancing supply and demand a

Applications

ACT: Automated CPS Testing for Open-Source Robotic Platforms

arXiv:2604.11708v1 Announce Type: new Abstract: Open-source software for cyber-physical systems (CPS) often lacks robust testing involving robotic platforms, resulting in critical errors that remain u

applicationsarxiv-cs-ro

ActDistill: General Action-Guided Self-Derived Distillation for Efficient Vision-Language-Action Models

arXiv:2511.18082v3 Announce Type: replace Abstract: Recent Vision-Language-Action (VLA) models have shown impressive flexibility and generalization, yet their deployment in robotic manipulation remain

tutorialsarxiv-cs-cv

Active Bayesian Inference for Robust Control under Sensor False Data Injection Attacks

arXiv:2604.11410v1 Announce Type: new Abstract: We present a framework for bridging the gap between sensor attack detection and recovery in cyber-physical systems. The proposed framework models modern

Safety

Active Diffusion Matching: Score-based Iterative Alignment of Cross-Modal Retinal Images

arXiv:2604.10084v1 Announce Type: new Abstract: Objective: The study aims to address the challenge of aligning Standard Fundus Images (SFIs) and Ultra-Widefield Fundus Images (UWFIs), which is difficu

safetyarxiv-cs-cv

Active Inference with a Self-Prior in the Mirror-Mark Task

arXiv:2604.09673v1 Announce Type: cross Abstract: The mirror self-recognition test evaluates whether a subject touches a mark on its own body that is visible only in a mirror, and is widely used as an

ActorMind: Emulating Human Actor Reasoning for Speech Role-Playing

arXiv:2604.11103v1 Announce Type: cross Abstract: Role-playing has garnered rising attention as it provides a strong foundation for human-machine interaction and facilitates sociological research. How

ADAM: A Systematic Data Extraction Attack on Agent Memory via Adaptive Querying

arXiv:2604.09747v1 Announce Type: cross Abstract: Large Language Model (LLM) agents have achieved rapid adoption and demonstrated remarkable capabilities across a wide range of applications. To improv

agentsarxiv-cs-ai

Adapting 2D Multi-Modal Large Language Model for 3D CT Image Analysis

arXiv:2604.10233v1 Announce Type: cross Abstract: 3D medical image analysis is of great importance in disease diagnosis and treatment. Recently, multimodal large language models (MLLMs) have exhibited

Safety

Adaptive Bidding Policies for First-Price Auctions with Budget Constraints under Non-stationarity

arXiv:2505.02796v2 Announce Type: replace-cross Abstract: We study how a budget-constrained bidder should learn to adaptively bid in repeated first-price auctions to maximize her cumulative payoff. Th

safetyarxiv-cs-lg

Adaptive H-EFT-VA: A Provably Safe Trajectory Through the Trainability-Expressibility Landscape of Variational Quantum Algorithms

arXiv:2604.10607v1 Announce Type: cross Abstract: H-EFT-VA established a physics-informed solution to the Barren Plateau (BP) problem via a hierarchical EFT UV-cutoff, guaranteeing gradient variance i

Adaptive Multi-Expert Reasoning via Difficulty-Aware Routing and Uncertainty-Guided Aggregation

arXiv:2604.10335v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong performance in math reasoning benchmarks, but their performance varies inconsistently across problems wi

researcharxiv-cs-cl

AdaQE-CG: Adaptive Query Expansion for Web-Scale Generative AI Model and Data Card Generation

arXiv:2604.09617v1 Announce Type: new Abstract: Transparent and standardized documentation is essential for building trustworthy generative AI (GAI) systems. However, existing automated methods for ge

ADD for Multi-Bit Image Watermarking

arXiv:2604.11491v1 Announce Type: cross Abstract: As generative models enable rapid creation of high-fidelity images, societal concerns about misinformation and authenticity have intensified. A promis

Adoption and Effectiveness of AI-Based Anomaly Detection for Cross Provider Health Data Exchange

arXiv:2604.09630v1 Announce Type: cross Abstract: This study investigates the adoption and effectiveness of AI-based anomaly detection in cross-provider electronic health record (EHR) environments. It

Advancing Polish Language Modeling through Tokenizer Optimization in the Bielik v3 7B and 11B Series

arXiv:2604.10799v1 Announce Type: cross Abstract: The development of the Bielik v3 PL series, encompassing both the 7B and 11B parameter variants, represents a significant milestone in the field of la

Advancing Reasoning in Diffusion Language Models with Denoising Process Rewards

arXiv:2510.01544v2 Announce Type: replace Abstract: Diffusion-based large language models offer a non-autoregressive alternative for text generation, but enabling them to perform complex reasoning rem

AdvDINO: Domain-Adversarial Self-Supervised Representation Learning for Spatial Proteomics

arXiv:2508.04955v2 Announce Type: replace-cross Abstract: Self-supervised learning (SSL) has emerged as a powerful approach for learning visual representations without manual annotations. However, the

Adversarial Robustness of Graph Transformers

arXiv:2407.11764v2 Announce Type: replace Abstract: Existing studies have shown that Message-Passing Graph Neural Networks (MPNNs) are highly susceptible to adversarial attacks. In contrast, despite t

Adversarial Video Promotion Against Text-to-Video Retrieval

arXiv:2508.06964v3 Announce Type: replace Abstract: Thanks to the development of cross-modal models, text-to-video retrieval (T2VR) is advancing rapidly, but its robustness remains largely unexamined.

researcharxiv-cs-cv

AdvSynGNN: Structure-Adaptive Graph Neural Nets via Adversarial Synthesis and Self-Corrective Propagation

arXiv:2602.17071v2 Announce Type: replace-cross Abstract: Graph neural networks frequently encounter significant performance degradation when confronted with structural noise or non-homophilous topolo

AEG: A Baremetal Framework for AI Acceleration via Direct Hardware Access in Heterogeneous Accelerators

arXiv:2604.09565v1 Announce Type: cross Abstract: This paper introduces a unified, hardware-independent baremetal runtime architecture designed to enable high-performance machine learning (ML) inferen