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As everyone knows, the internet has millions of images of art galleries filled with paintings of otters sitting on airplanes, which is the o…

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As everyone knows, the internet has millions of images of art galleries filled with paintings of otters sitting on airplanes, which is the only reason these stochastic parrot AIs can produce outputs l

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Attention-based Multi-modal Deep Learning Model of Spatio-temporal Crop Yield Prediction with Satellite, Soil and Climate Data

DGX agent

arXiv:2604.19217v1 Announce Type: cross Abstract: Crop yield prediction is one of the most important challenge, which is crucial to world food security and policy-making decisions. The conventional fo

safetyarxiv-cs-ai

22 Apr 2026

Agents

Autonomous UAV Pipeline Near-proximity Inspection via Disturbance-Aware Predictive Visual Servoing

arXiv:2604.19618v1 Announce Type: new Abstract: Reliable pipeline inspection is critical to safe energy transportation, but is constrained by long distances, complex terrain, and risks to human inspec

agentsarxiv-cs-ro

Bayesian Event-Based Model for Disease Subtype and Stage Inference

arXiv:2512.03467v2 Announce Type: replace Abstract: Chronic diseases often progress differently across patients. Rather than randomly varying, there are typically a small number of subtypes for how a

applicationsarxiv-cs-lg

BEAT: Tokenizing and Generating Symbolic Music by Uniform Temporal Steps

arXiv:2604.19532v1 Announce Type: cross Abstract: Tokenizing music to fit the general framework of language models is a compelling challenge, especially considering the diverse symbolic structures in

Benchmarking Vision Foundation Models for Domain-Generalizable Face Anti-Spoofing

arXiv:2604.19196v1 Announce Type: new Abstract: Face Anti-Spoofing (FAS) remains challenging due to the requirement for robust domain generalization across unseen environments. While recent trends lev

Beyond Coefficients: Forecast-Necessity Testing for Interpretable Causal Discovery in Nonlinear Time-Series Models

arXiv:2604.18751v1 Announce Type: cross Abstract: Nonlinear machine-learning models are increasingly used to discover causal relationships in time-series data, yet the interpretation of their outputs

applicationsarxiv-cs-ai

Beyond Rating: A Comprehensive Evaluation and Benchmark for AI Reviews

model-releasesarxiv-cs-cl

arXiv:2604.19502v1 Announce Type: new Abstract: The rapid adoption of Large Language Models (LLMs) has spurred interest in automated peer review; however, progress is currently stifled by benchmarks t

Beyond the Bellman Fixed Point: Geometry and Fast Policy Identification in Value Iteration

arXiv:2604.17457v2 Announce Type: replace-cross Abstract: Dynamic programming is one of the most fundamental methodologies for solving Markov decision problems. Among its many variants, Q-value iterat

Byzantine-tolerant distributed learning of finite mixture models

model-releasesarxiv-cs-lg

arXiv:2407.13980v3 Announce Type: replace-cross Abstract: Traditional statistical methods need to be updated to work with modern distributed data storage paradigms. A common approach is the split-and-

Centralized Copy-Paste: Enhanced Data Augmentation Strategy for Wildland Fire Semantic Segmentation

arXiv:2507.06321v2 Announce Type: replace Abstract: Collecting and annotating images for the purpose of training segmentation models is often cost prohibitive. In the domain of wildland fire science,

Chimera: Neuro-Symbolic Attention Primitives for Trustworthy Dataplane Intelligence

arXiv:2602.12851v3 Announce Type: replace-cross Abstract: Deploying expressive learning models directly on programmable dataplanes promises line-rate, low-latency traffic analysis but remains hindered

Colour Extraction Pipeline for Odonates using Computer Vision

arXiv:2604.18725v1 Announce Type: new Abstract: The correlation between insect morphological traits and climate has been documented in physiological studies, but such studies remain limited by the tim

Concept Inconsistency in Dermoscopic Concept Bottleneck Models: A Rough-Set Analysis of the Derm7pt Dataset

model-releasesarxiv-cs-cv

arXiv:2604.19323v1 Announce Type: cross Abstract: Concept Bottleneck Models (CBMs) route predictions exclusively through a clinically grounded concept layer, binding interpretability to concept-label

Conditional Diffusion Modeling with Attention for Probabilistic Battery Capacity Prediction under Real-World Condition

arXiv:2510.17414v2 Announce Type: replace Abstract: Accurate prediction of lithium-ion battery capacity and its associated uncertainty is essential for reliable battery management but remains challeng

applicationsarxiv-cs-lg

Council Mode: Mitigating Hallucination and Bias in LLMs via Multi-Agent Consensus

model-releasesarxiv-cs-ai

arXiv:2604.02923v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs), particularly those employing Mixture-of-Experts (MoE) architectures, have achieved remarkable capabilities acros

Counting Worlds Branching Time Semantics for post-hoc Bias Mitigation in generative AI

arXiv:2604.19431v1 Announce Type: cross Abstract: Generative AI systems are known to amplify biases present in their training data. While several inference-time mitigation strategies have been propose

DASH-KV: Accelerating Long-Context LLM Inference via Asymmetric KV Cache Hashing

arXiv:2604.19351v1 Announce Type: new Abstract: The quadratic computational complexity of the standard attention mechanism constitutes a fundamental bottleneck for large language models in long-contex

researcharxiv-cs-cl

Debiased neural operators for estimating functionals

arXiv:2604.19296v1 Announce Type: new Abstract: Neural operators are widely used to approximate solution maps of complex physical systems. In many applications, however, the goal is not to recover the

safetyarxiv-cs-lg

Decomposed Trust: Privacy, Adversarial Robustness, Ethics, and Fairness in Low-Rank LLMs

arXiv:2511.22099v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have driven major advances across domains, yet their massive size hinders deployment in resource-constrained sett

Deep sprite-based image models: An analysis

model-releasesarxiv-cs-cv

arXiv:2604.19480v1 Announce Type: new Abstract: While foundation models drive steady progress in image segmentation and diffusion algorithms compose always more realistic images, the seemingly simple

Deep Supervised Contrastive Learning of Pitch Contours for Robust Pitch Accent Classification in Seoul Korean

model-releasesarxiv-cs-cl

arXiv:2604.19477v1 Announce Type: cross Abstract: The intonational structure of Seoul Korean has been defined with discrete tonal categories within the Autosegmental-Metrical model of intonational pho

DeltaSeg: Tiered Attention and Deep Delta Learning for Multi-Class Structural Defect Segmentation

arXiv:2604.18745v1 Announce Type: new Abstract: Automated segmentation of structural defects from visual inspection imagery remains challenging due to the diversity of damage types, extreme class imba

Diagnosable ColBERT: Debugging Late-Interaction Retrieval Models Using a Learned Latent Space as Reference

arXiv:2604.19566v1 Announce Type: cross Abstract: Reliable biomedical and clinical retrieval requires more than strong ranking performance: it requires a practical way to find systematic model failure

safetyarxiv-cs-cl

DP-FlogTinyLLM: Differentially private federated log anomaly detection using Tiny LLMs

model-releasesarxiv-cs-ai

arXiv:2604.19118v1 Announce Type: cross Abstract: Modern distributed systems generate massive volumes of log data that are critical for detecting anomalies and cyber threats. However, in real world se

Early Pruning for Public Transport Routing

arXiv:2603.12592v2 Announce Type: replace-cross Abstract: Routing algorithms for public transport, particularly the widely used RAPTOR and its variants, often face performance bottlenecks during the t

Hardware

Efficient Mixture-of-Experts LLM Inference with Apple Silicon NPUs

arXiv:2604.18788v1 Announce Type: new Abstract: Apple Neural Engine (ANE) is a dedicated neural processing unit (NPU) present in every Apple Silicon chip. Mixture-of-Experts (MoE) LLMs improve inferen

hardwarearxiv-cs-lg

Evaluating Answer Leakage Robustness of LLM Tutors against Adversarial Student Attacks

model-releasesarxiv-cs-ai

arXiv:2604.18660v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in education, yet their default helpfulness often conflicts with pedagogical principles. Prior work

Evaluating LLM-Generated Obfuscated XSS Payloads for Machine Learning-Based Detection

arXiv:2604.19526v1 Announce Type: cross Abstract: Cross-site scripting (XSS) remains a persistent web security vulnerability, especially because obfuscation can change the surface form of a malicious

researcharxiv-cs-lg

Local Ai

Evaluation-driven Scaling for Scientific Discovery

arXiv:2604.19341v1 Announce Type: cross Abstract: Language models are increasingly used in scientific discovery to generate hypotheses, propose candidate solutions, implement systems, and iteratively

local-aiarxiv-cs-ai

ExpertGen: Scalable Sim-to-Real Expert Policy Learning from Imperfect Behavior Priors

arXiv:2603.15956v2 Announce Type: replace-cross Abstract: Learning generalizable and robust behavior cloning policies requires large volumes of high-quality robotics data. While human demonstrations (

FairTree: Subgroup Fairness Auditing of Machine Learning Models with Bias-Variance Decomposition

arXiv:2604.19357v1 Announce Type: new Abstract: The evaluation of machine learning models typically relies mainly on performance metrics based on loss functions, which risk to overlook changes in perf

safetyarxiv-cs-lg

Fast estimation of Gaussian mixture components via centering and singular value thresholding

arXiv:2604.19091v1 Announce Type: cross Abstract: Estimating the number of components is a fundamental challenge in unsupervised learning, particularly when dealing with high-dimensional data with man

researcharxiv-cs-lg

Feature Perturbation Pool-based Fusion Network for Unified Multi-Class Industrial Defect Detection

arXiv:2604.19259v1 Announce Type: new Abstract: Multi-class defect detection constitutes a critical yet challenging task in industrial quality inspection, where existing approaches typically suffer fr

FedSEA: Achieving Benefit of Parallelization in Federated Online Learning

arXiv:2604.19336v1 Announce Type: new Abstract: Online federated learning (OFL) has emerged as a popular framework for decentralized decision-making over continuous data streams without compromising c

researcharxiv-cs-lg

Fine-Tuning Code Language Models to Detect Cross-Language Bugs

arXiv:2507.21954v2 Announce Type: replace-cross Abstract: Multilingual programming, which involves using multiple programming languages (PLs) in a single project, is increasingly common due to its ben

Formally Verified Patent Analysis via Dependent Type Theory: Machine-Checkable Certificates from a Hybrid AI + Lean 4 Pipeline

arXiv:2604.18882v1 Announce Type: new Abstract: We present a formally verified framework for patent analysis as a hybrid AI + Lean 4 pipeline. The DAG-coverage core (Algorithm 1b) is fully machine-ver

applicationsarxiv-cs-ai

Forward Dynamics of Variable Topology Mechanisms - The Case of Constraint Activation

arXiv:2604.19419v1 Announce Type: new Abstract: Many mechanical systems exhibit changes in their kinematic topology altering the mobility. Ideal contact is the best known cause, but also stiction and

researcharxiv-cs-ro

From Top-1 to Top-K: A Reproducibility Study and Benchmarking of Counterfactual Explanations for Recommender Systems

arXiv:2604.19663v1 Announce Type: cross Abstract: Counterfactual explanations (CEs) provide an intuitive way to understand recommender systems by identifying minimal modifications to user-item interac

applicationsarxiv-cs-lg

GenerativeMPC: VLM-RAG-guided Whole-Body MPC with Virtual Impedance for Bimanual Mobile Manipulation

model-releasesarxiv-cs-ro

arXiv:2604.19522v1 Announce Type: new Abstract: Bimanual mobile manipulation requires a seamless integration between high-level semantic reasoning and safe, compliant physical interaction - a challeng

HarDBench: A Benchmark for Draft-Based Co-Authoring Jailbreak Attacks for Safe Human-LLM Collaborative Writing

model-releasesarxiv-cs-cl

arXiv:2604.19274v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as co-authors in collaborative writing, where users begin with rough drafts and rely on LLMs to compl

Heterogeneity-Aware Personalized Federated Learning for Industrial Predictive Analytics

model-releasesarxiv-cs-lg

arXiv:2604.19451v1 Announce Type: new Abstract: Federated prognostics enable clients (e.g., companies, factories, and production lines) to collaboratively develop a failure time prediction model while

How does the optimizer implicitly bias the model merging loss landscape?

arXiv:2510.04686v2 Announce Type: replace-cross Abstract: Model merging combines independent solutions with different capabilities into a single one while maintaining the same inference cost. Two popu

How far are we from agents that can self-generate world knowledge? The work proposes an outcome-based reward that measures how much an agent…

How far are we from agents that can self-generate world knowledge? The work proposes an outcome-based reward that measures how much an agent's self-generated world knowledge actually improves its task

model-releasesdair-ai--x

Hugging Face Releases ml-intern: An Open-Source AI Agent that Automates the LLM Post-Training Workflow [The 'AI Intern' that actually ships …

model-releasesclem-delangue--x

Hugging Face Releases ml-intern: An Open-Source AI Agent that Automates the LLM Post-Training Workflow [The 'AI Intern' that actually ships SOTA models ] This isn't just another ML Research Loop wrapp

Human-Machine Co-Boosted Bug Report Identification with Mutualistic Neural Active Learning

arXiv:2604.18862v1 Announce Type: cross Abstract: Bug reports, encompassing a wide range of bug types, are crucial for maintaining software quality. However, the increasing complexity and volume of bu

applicationsarxiv-cs-ai

Impact of large language models on peer review opinions from a fine-grained perspective: Evidence from top conference proceedings in AI

arXiv:2604.19578v1 Announce Type: cross Abstract: With the rapid advancement of Large Language Models (LLMs), the academic community has faced unprecedented disruptions, particularly in the realm of a

Local Ai

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network

arXiv:2604.19240v1 Announce Type: new Abstract: Industrial surface defect detection often suffers from limited defect samples, severe long-tailed distributions, and difficulties in accurately localizi

local-aiarxiv-cs-ai