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Neural posterior estimation of the neutrino direction in IceCube using transformer-encoded normalizing flows on the sphere

arXiv:2604.19846v1 Announce Type: cross Abstract: IceCube is a cubic-kilometer-scale neutrino detector located at the geographic South Pole. A precise directional reconstruction of IceCube neutrinos i

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Human DGX agent

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NeuroSymActive: Differentiable Neural-Symbolic Reasoning with Active Exploration for Knowledge Graph Question Answering

DGX agent

arXiv:2602.15353v2 Announce Type: replace-cross Abstract: Large pretrained language models and neural reasoning systems have advanced many natural language tasks, yet they remain challenged by knowled

safetyarxiv-cs-ai

23 Apr 2026

'Newspaper Eat' Means 'Not Tasty': A Taxonomy and Benchmark for Coded Language in Real-World Chinese Online Reviews

model-releasesarxiv-cs-cl

arXiv:2601.19932v2 Announce Type: replace Abstract: Coded language is an important part of human communication. It refers to cases where users intentionally encode meaning so that the surface text dif

Applications

No More Marching: Learning Humanoid Locomotion for Short-Range SE(2) Targets

arXiv:2508.14098v2 Announce Type: replace-cross Abstract: Humanoids operating in real-world workspaces must frequently execute task-driven, short-range movements to SE(2) target poses. To be practical

applicationsarxiv-cs-ai

Normalizing Flows with Iterative Denoising

arXiv:2604.20041v1 Announce Type: cross Abstract: Normalizing Flows (NFs) are a classical family of likelihood-based methods that have received revived attention. Recent efforts such as TARFlow have s

Not all ANIMALs are equal: metaphorical framing through source domains and semantic frames

arXiv:2604.20454v1 Announce Type: new Abstract: Metaphors are powerful framing devices, yet their source domains alone do not fully explain the specific associations they evoke. We argue that the inte

Object Referring-Guided Scanpath Prediction with Perception-Enhanced Vision-Language Models

arXiv:2604.20361v1 Announce Type: new Abstract: Object Referring-guided Scanpath Prediction (ORSP) aims to predict the human attention scanpath when they search for a specific target object in a visua

Occupancy Reward Shaping: Improving Credit Assignment for Offline Goal-Conditioned Reinforcement Learning

arXiv:2604.20627v1 Announce Type: new Abstract: The temporal lag between actions and their long-term consequences makes credit assignment a challenge when learning goal-directed behaviors from data. G

safetyarxiv-cs-lg

OISMA: On-the-fly In-memory Stochastic Multiplication Architecture for Matrix-Multiplication Workloads

arXiv:2508.08822v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) models are currently driven by a significant upscaling of their complexity, with massive matrix-multiplication wo

OMIBench: Benchmarking Olympiad-Level Multi-Image Reasoning in Large Vision-Language Model

model-releasesarxiv-cs-ai

arXiv:2604.20806v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) have made substantial advances in reasoning tasks at the Olympiad level. Nevertheless, current Olympiad-level mul

On Bayesian Softmax-Gated Mixture-of-Experts Models

model-releasesarxiv-cs-lg

arXiv:2604.20551v1 Announce Type: cross Abstract: Mixture-of-experts models provide a flexible framework for learning complex probabilistic input-output relationships by combining multiple expert mode

Applications

On-Meter Graph Machine Learning: A Case Study of PV Power Forecasting for Grid Edge Intelligence

arXiv:2604.19800v1 Announce Type: cross Abstract: This paper presents a detailed study of how graph neural networks can be used on edge intelligent meters in a microgrid to forecast photovoltaic power

applicationsarxiv-cs-ai

On the definition and importance of interpretability in scientific machine learning

arXiv:2505.13510v3 Announce Type: replace Abstract: Though neural networks trained on large datasets have been successfully used to describe and predict many physical phenomena, there is a sense among

researcharxiv-cs-lg

On the Existence of Universal Simulators of Attention

arXiv:2506.18739v2 Announce Type: replace-cross Abstract: Previous work on the learnability of transformers extemdash focused primarily on examining their ability to approximate specific algorithmic p

On the Impact of Face Segmentation-Based Background Removal on Recognition and Morphing Attack Detection

arXiv:2604.20585v1 Announce Type: new Abstract: This study investigates the impact of face image background correction through segmentation on face recognition and morphing attack detection performanc

On the Quantization Robustness of Diffusion Language Models in Coding Benchmarks

arXiv:2604.20079v1 Announce Type: cross Abstract: Auto-regressive Large Language Models (LLMs) achieve strong performance on coding tasks, but incur high memory and inference costs. Diffusion-based la

On the Stability and Generalization of First-order Bilevel Minimax Optimization

arXiv:2604.20115v1 Announce Type: cross Abstract: Bilevel optimization and bilevel minimax optimization have recently emerged as unifying frameworks for a range of machine-learning tasks, including hy

Agents

Onboard Wind Estimation for Small UAVs Equipped with Low-Cost Sensors: An Aerodynamic Model-Integrated Filtering Approach

arXiv:2604.20290v1 Announce Type: new Abstract: To enable autonomous wind estimation for energy-efficient flight in small unmanned aerial vehicles (UAVs), this study proposes a method that estimates f

agentsarxiv-cs-ro

Online CS-based SAR Edge-Mapping

arXiv:2604.19989v1 Announce Type: new Abstract: With modern defense applications increasingly relying on inexpensive, small Unmanned Aerial Vehicles (UAVs), a major challenge lies in designing intelli

Local Ai

Online Structure Learning and Planning for Autonomous Robot Navigation using Active Inference

arXiv:2510.09574v2 Announce Type: replace Abstract: Autonomous navigation in unfamiliar environments requires robots to simultaneously explore, localise, and plan under uncertainty, without relying on

local-aiarxiv-cs-ro

Online Survival Analysis: A Bandit Approach under Cox PH Model

arXiv:2604.20296v1 Announce Type: cross Abstract: Survival analysis is a widely used statistical framework for modeling time-to-event data under censoring. Classical methods, such as the Cox proportio

researcharxiv-cs-lg

ONOTE: Benchmarking Omnimodal Notation Processing for Expert-level Music Intelligence

model-releasesarxiv-cs-ai

arXiv:2604.20719v1 Announce Type: cross Abstract: Omnimodal Notation Processing (ONP) represents a unique frontier for omnimodal AI due to the rigorous, multi-dimensional alignment required across aud

OnSiteVRU: A High-Resolution Trajectory Dataset for High-Density Vulnerable Road Users

arXiv:2503.23365v2 Announce Type: replace Abstract: With the acceleration of urbanization and the growth of transportation demands, the safety of vulnerable road users (VRUs, such as pedestrians and c

safetyarxiv-cs-cv

Onyx: Cost-Efficient Disk-Oblivious ANN Search

arXiv:2604.20401v1 Announce Type: cross Abstract: Approximate nearest neighbor (ANN) search in AI systems increasingly handles sensitive data on third-party infrastructure. Trusted execution environme

Local Ai

Open-Architecture End-to-End System for Real-World Autonomous Robot Navigation

arXiv:2410.06239v3 Announce Type: replace Abstract: Enabling robots to autonomously navigate unknown, complex, and dynamic real-world environments presents several challenges, including imperfect perc

local-aiarxiv-cs-ro

Hardware

OpenCLAW-P2P v6.0: Resilient Multi-Layer Persistence, Live Reference Verification, and Production-Scale Evaluation of Decentralized AI Peer Review

arXiv:2604.19792v1 Announce Type: new Abstract: This paper presents OpenCLAW-P2P v6.0, a comprehensive evolution of the decentralized collective-intelligence platform in which autonomous AI agents pub

hardwarearxiv-cs-ai

Opportunistic Bone-Loss Screening from Routine Knee Radiographs Using a Multi-Task Deep Learning Framework with Sensitivity-Constrained Threshold Optimization

arXiv:2604.20268v1 Announce Type: new Abstract: Background: Osteoporosis and osteopenia are often undiagnosed until fragility fractures occur. Dual-energy X-ray absorptiometry (DXA) is the reference s

Optimal Single-Policy Sample Complexity and Transient Coverage for Average-Reward Offline RL

model-releasesarxiv-cs-lg

arXiv:2506.20904v2 Announce Type: replace Abstract: We study offline reinforcement learning in average-reward MDPs, which presents increased challenges from the perspectives of distribution shift and

Optimizing Data Augmentation for Real-Time Small UAV Detection: A Lightweight Context-Aware Approach

arXiv:2604.19999v1 Announce Type: new Abstract: Visual detection of Unmanned Aerial Vehicles (UAVs) is a critical task in surveillance systems due to their small physical size and environmental challe

Optimizing User Profiles via Contextual Bandits for Retrieval-Augmented LLM Personalization

arXiv:2601.12078v2 Announce Type: replace Abstract: Large language models (LLMs) excel at general-purpose tasks, yet adapting their responses to individual users remains challenging. Retrieval augment

Option Pricing on Noisy Intermediate-Scale Quantum Computers: A Quantum Neural Network Approach

model-releasesarxiv-cs-lg

arXiv:2604.19832v1 Announce Type: cross Abstract: In a global derivatives market with notional values in the hundreds of trillions of dollars, the accuracy and efficiency of pricing models are of fund

ORPHEAS: A Cross-Lingual Greek-English Embedding Model for Retrieval-Augmented Generation

arXiv:2604.20666v1 Announce Type: cross Abstract: Effective retrieval-augmented generation across bilingual Greek--English applications requires embedding models capable of capturing both domain-speci

safetyarxiv-cs-ai

OThink-SRR1: Search, Refine and Reasoning with Reinforced Learning for Large Language Models

arXiv:2604.19766v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) expands the knowledge of Large Language Models (LLMs), yet current static retrieval methods struggle with complex

Over-Refusal and Representation Subspaces: A Mechanistic Analysis of Task-Conditioned Refusal in Aligned LLMs

arXiv:2603.27518v2 Announce Type: replace Abstract: Aligned language models that are trained to refuse harmful requests also exhibit over-refusal: they decline safe instructions that seemingly resembl

Applications

Overcoming the Modality Gap in Context-Aided Forecasting

arXiv:2603.12451v3 Announce Type: replace Abstract: Context-aided forecasting (CAF) holds promise for integrating domain knowledge and forward-looking information, enabling AI systems to surpass tradi

applicationsarxiv-cs-lg

OVPD: A Virtual-Physical Fusion Testing Dataset of OnSite Auton-omous Driving Challenge

model-releasesarxiv-cs-ro

arXiv:2604.20423v1 Announce Type: new Abstract: The rapid iteration of autonomous driving algorithms has created a growing demand for high-fidelity, replayable, and diagnosable testing data. However,

Agents

pAI/MSc: ML Theory Research with Humans on the Loop

arXiv:2604.20622v1 Announce Type: new Abstract: We present pAI/MSc, an open-source, customizable, modular multi-agent system for academic research workflows. Our goal is not autonomous scientific idea

agentsarxiv-cs-ai

Pairing Regularization for Mitigating Many-to-One Collapse in GANs

arXiv:2604.20130v1 Announce Type: cross Abstract: Mode collapse remains a fundamental challenge in training generative adversarial networks (GANs). While existing works have primarily focused on inter

Parallel-SFT: Improving Zero-Shot Cross-Programming-Language Transfer for Code RL

model-releasesarxiv-cs-cl

arXiv:2604.20835v1 Announce Type: new Abstract: Modern language models demonstrate impressive coding capabilities in common programming languages (PLs), such as C++ and Python, but their performance i

ParetoSlider: Diffusion Models Post-Training for Continuous Reward Control

arXiv:2604.20816v1 Announce Type: cross Abstract: Reinforcement Learning (RL) post-training has become the standard for aligning generative models with human preferences, yet most methods rely on a si

Participatory provenance as representational auditing for AI-mediated public consultation

arXiv:2604.20711v1 Announce Type: new Abstract: Artificial intelligence is increasingly deployed to synthesize large-scale public input in policy consultations and participatory processes. Yet no form

safetyarxiv-cs-ai

Passive Variable Impedance For Shared Control

arXiv:2604.20557v1 Announce Type: new Abstract: Shared Control methods often use impedance control to track target poses in a robotic manipulator. The guidance behavior of such controllers is shaped b

researcharxiv-cs-ro

PASTA: A Patch-Agnostic Twofold-Stealthy Backdoor Attack on Vision Transformers

arXiv:2604.20047v1 Announce Type: new Abstract: Vision Transformers (ViTs) have achieved remarkable success across vision tasks, yet recent studies show they remain vulnerable to backdoor attacks. Exi

Peer-Preservation in Frontier Models

model-releasesarxiv-cs-ai

arXiv:2604.19784v1 Announce Type: cross Abstract: Recently, it has been found that frontier AI models can resist their own shutdown, a behavior known as self-preservation. We extend this concept to th

Personalized electric vehicle energy consumption estimation framework that integrates driver behavior with map data

arXiv:2604.20764v1 Announce Type: cross Abstract: This paper presents a personalized Battery Electric Vehicle (BEV) energy consumption estimation framework that integrates map-based contextual feature

researcharxiv-cs-lg

PFGNet: A Fully Convolutional Frequency-Guided Peripheral Gating Network for Efficient Spatiotemporal Predictive Learning

arXiv:2602.20537v3 Announce Type: replace Abstract: Spatiotemporal predictive learning (STPL) aims to forecast future frames from past observations and is essential across a wide range of applications

Phase 1 Implementation of LLM-generated Discharge Summaries showing high Adoption in a Dutch Academic Hospital

arXiv:2604.19774v1 Announce Type: cross Abstract: Writing discharge summaries to transfer medical information is an important but time-consuming process that can be assisted by Large Language Models (

Tutorials

Physics-Conditioned Synthesis of Internal Ice-Layer Thickness for Incomplete Layer Traces

arXiv:2604.20783v1 Announce Type: new Abstract: Internal ice layers imaged by radar provide key evidence of snow accumulation and ice dynamics, but radar-derived layer boundary observations are often

tutorialsarxiv-cs-lg