Search: “papers”

OpenWebRL: Demystifying Online Multi-turn Reinforcement Learning for Visual Web Agents

arXiv:2606.02031v1 Announce Type: cross Abstract: Building capable visual web agents requires long-horizon reasoning, precise grounding, and robust interaction with dynamic real-world websites. Despit

Safety

Optimal Bayesian Stopping for Efficient Inference of Consistent LLM Answers

DGX agent

arXiv:2602.05395v2 Announce Type: replace-cross Abstract: A simple strategy for improving LLM accuracy, especially in math and reasoning problems, is to sample multiple responses and submit the answer

safetyarxiv-cs-ai

2 Jun 2026

Parameter-efficient Dual-encoder Architecture with Differentiable Choquet Integral Fusion for Underwater Acoustic Classification

model-releasesarxiv-cs-lg

arXiv:2606.02341v1 Announce Type: cross Abstract: Underwater acoustic classification has a wide array of oceanic applications, but faces challenges due to an increasingly complex acoustic environment.

PathCRF: Ball-Free Soccer Event Detection via Possession Path Inference from Player Trajectories

arXiv:2602.12080v2 Announce Type: replace Abstract: Despite recent advances in AI, event data collection in soccer still relies heavily on labor-intensive manual annotation. Although prior work has ex

Peacemaker at ATE-IT: Automatic term extraction from Italian text for waste management data using encoder model

arXiv:2606.01469v1 Announce Type: new Abstract: The development of automatic term extraction has become increasingly important in modern technology. Automatic term extraction can be found in virtually

researcharxiv-cs-cl

Permissive Safety Through Trusted Inference: Verifiable Belief-Space Neural Safety Filters for Assured Interactive Robotics

arXiv:2606.02562v1 Announce Type: cross Abstract: Autonomous robots that interact with people must make safe and efficient decisions under human-induced uncertainty, such as their preferences, goals,

Persona Attack: Incremental Memory Injection Jailbreak Attack against Large Language Models

arXiv:2606.00150v1 Announce Type: cross Abstract: As Large Language Models evolve for user convenience, vulnerability to jailbreak attacks continues to be reported despite ongoing efforts in safety tr

Physics-Aware Linearized ADMM and Its Unrolling

arXiv:2606.01652v1 Announce Type: cross Abstract: Recently, partial differential equations (PDEs) have been used to directly model the measurement process in signal processing, although their evaluati

researcharxiv-cs-cv

Applications

Physics-Informed Deep Learning for Entropy Prediction in Heterogeneous Systems: Thermodynamic and Information-Theoretic Case Studies

arXiv:2606.01179v1 Announce Type: cross Abstract: Entropy production governs irreversibility and uncertainty in both physical and information-theoretic systems. While Physics-Informed Neural Networks

applicationsarxiv-cs-ai

Tutorials

Physics-Informed Residuals for Adaptive Mesh Refinement in Finite-Difference PDE Solvers

arXiv:2606.02475v1 Announce Type: cross Abstract: Classical finite-difference solvers remain reliable tools for partial differential equations, but their efficiency depends on where mesh resolution is

tutorialsarxiv-cs-lg

Agents

PillarDETR: YOLO-Backbone and RT-DETR Head for Real-Time 3D Object Detection

arXiv:2606.01757v1 Announce Type: new Abstract: Real-time 3D object detection is a critical component for the safe operation of autonomous driving systems and robotics. While LiDAR point clouds provid

agentsarxiv-cs-cv

Pinterest Canvas: Large-Scale Image Generation at Pinterest

arXiv:2603.06453v2 Announce Type: replace Abstract: While recent image generation models demonstrate a remarkable ability to handle a wide variety of image generation tasks, this flexibility makes the

researcharxiv-cs-cv

Applications

Planar Symmetric Pattern Generation

arXiv:2606.02073v1 Announce Type: new Abstract: Generating objects with specific symmetries is essential in various real-world scenarios. However, adapting existing 2D continuous representations to en

applicationsarxiv-cs-lg

Pool-Select-Refine: Allocation-Aware Generative Dataset Distillation with Soft-Label-Guided Latent Refinement

arXiv:2606.01920v1 Announce Type: new Abstract: Diffusion-based dataset distillation has recently emerged as a promising paradigm for condensing large-scale datasets into compact synthetic sets. By le

safetyarxiv-cs-cv

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants

arXiv:2508.08337v3 Announce Type: replace-cross Abstract: Algorithmic fairness research has largely framed unfairness as discrimination along sensitive attributes. However, this approach limits visibi

Position: Current Benchmarking Hinders Real Progress in Deep Learning for Time Series Forecasting

arXiv:2512.22702v2 Announce Type: replace Abstract: Deep learning models have grown popular in time series applications. However, the large quantity of newly proposed architectures and the often contr

local-aiarxiv-cs-lg

Position: Neglecting the Sustainability of AI is Fuelling a Global AI Arms Race

arXiv:2502.20016v2 Announce Type: replace Abstract: Sustainability encompasses three key facets: economic, environmental, and social. However, the nascent discourse on sustainable artificial intellige

Post-Deterministic Distributed Systems: A New Foundation for Trustworthy Autonomous Infrastructure

arXiv:2606.01722v1 Announce Type: cross Abstract: For decades, distributed systems have typically assumed that correct participants execute protocol-specified behavior with stable, externally defined,

Hardware

Predicting Future Utility: Global Combinatorial Optimization for Task-Agnostic KV Cache Eviction

arXiv:2602.08585v2 Announce Type: replace-cross Abstract: Given the quadratic complexity of attention, KV cache eviction is vital to accelerate model inference. Current KV cache eviction methods typic

hardwarearxiv-cs-ai

Principled Synthetic Data Enables the First Scaling Laws for LLMs in Recommendation

arXiv:2602.07298v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) represent a promising frontier for recommender systems, yet their development has been impeded by the absence of

ProactiveLLM: Learning Active Interaction for Streaming Large Language Models

arXiv:2606.00523v1 Announce Type: new Abstract: Standard Large Language Models (LLMs) follow a read-then-generate paradigm, causing unnecessary latency and computation. Streaming LLMs alleviate this i

local-aiarxiv-cs-cl

ProductWebGen: Benchmarking Multimodal Product Webpage Generation

arXiv:2606.01022v1 Announce Type: cross Abstract: Crafting a product display webpage from a source product image, along with layout and visual content instructions, holds significant practical value f

ProjQ: Project-and-Quantize for Adapter-Aware LLM Compression

model-releasesarxiv-cs-lg

arXiv:2606.00494v1 Announce Type: new Abstract: Post-Training Quantization (PTQ) and Low-Rank Adaptation (LoRA) constitute the standard pipeline for efficient Large Language Model (LLM) deployment. Ho

PropLLM: Propagation-Aware Scene Reconstruction for Network Fault Diagnosis

arXiv:2606.00582v1 Announce Type: new Abstract: Network faults propagate layer by layer along topology and protocol dependencies, yet operations systems typically observe only symptomatic alerts at th

local-aiarxiv-cs-ai

Prototype Selection Using Topological Data Analysis

arXiv:2511.04873v2 Announce Type: replace-cross Abstract: Prototype selection methods compress a training set, but the existing taxonomy of condensation, edition, hybrid, competence-based, optimizatio

Provable Data Scaling Law for Meta Learning via Complexity Minimization

arXiv:2606.02008v1 Announce Type: cross Abstract: Pre-training has become a fundamental paradigm in modern machine learning, with one of its key empirical benefits being reduced downstream sample comp

PSG-Nav: Probabilistic Scene Graph Navigation via Multiverse Decision Making

arXiv:2606.01313v1 Announce Type: cross Abstract: Open-vocabulary navigation requires embodied agents to manage significant perception uncertainty stemming from semantic ambiguity and model errors. Ho

researcharxiv-cs-ai

Quality Audio Prototyping: a prototype system for unified sound retrieval and procedural generation

model-releasesarxiv-cs-lg

arXiv:2606.00629v1 Announce Type: cross Abstract: Sound design workflows frequently oscillate between time-consuming library searches and the complexity of procedural synthesis, with practitioners typ

Quantum Algorithm for Distributed Reduction of Entanglements (QADR): A Trainable and Simulation-Efficient QML Framework

arXiv:2606.01291v1 Announce Type: cross Abstract: Training Variational Quantum Circuits (VQCs) under Noisy Intermediate-Scale Quantum (NISQ) constraints introduces severe computational limitations: cl

Quantum Tunneling-Aware Machine Learning: Physics-Derived Noise Models for Robust Deployment

arXiv:2606.00741v1 Announce Type: cross Abstract: Transistor scaling is approaching a quantum-mechanical limit, as thin gate oxides induce electron leakage through quantum tunneling. Unlike convention

researcharxiv-cs-ai

Hardware

Quartet II: Accurate LLM Pre-Training in NVFP4 by Improved Unbiased Gradient Estimation

arXiv:2601.22813v2 Announce Type: replace Abstract: The NVFP4 lower-precision format, supported in hardware by NVIDIA Blackwell GPUs, promises to allow, for the first time, end-to-end fully-quantized

hardwarearxiv-cs-lg

RA-LWLM: Retrieval-Augmented In-Context Localization with Wireless Foundation Models

arXiv:2606.01899v1 Announce Type: cross Abstract: Wireless localization is a fundamental capability of sixth-generation (6G) networks. Conventional model-based methods require accurate modeling of the

local-aiarxiv-cs-ai

Recent Advances in Multi-modal 3D Intelligence: A Comprehensive Survey and Evaluation

arXiv:2310.15676v2 Announce Type: replace-cross Abstract: Multi-modal 3D Intelligence has gained considerable attention due to its wide applications in autonomous driving and world simulation, etc. Co

Regime-Adaptive Continual Learning for Portfolio Management

arXiv:2606.00143v1 Announce Type: cross Abstract: Financial markets are inherently non-stationary, exhibiting frequent regime shifts and structural changes that render traditional Portfolio Management

Revisiting Parameter-Based Knowledge Editing in Large Language Models: Theoretical Limits and Empirical Evidence

arXiv:2606.00570v1 Announce Type: cross Abstract: Parameter-based knowledge editing updates the internal knowledge of large language models (LLMs) via localized weight modifications and has attracted

Tutorials

Richer Representations for Neural Algorithmic Reasoning via Auxiliary Reconstruction

arXiv:2606.00559v1 Announce Type: cross Abstract: Neural algorithmic reasoning has emerged as a popular research direction. It aims to train neural networks to mimic the step-by-step behavior of class

tutorialsarxiv-cs-ai

RPCASSM: Robust PCA State Space Model For Infrared Small Target Detection

arXiv:2606.01689v1 Announce Type: cross Abstract: The detection and segmentation of infrared small targets have important application significance in the fields of surveillance and security, maritime

Applications

Safe-Subspace Pseudo-Label Refinement for Source-Free Graph Domain Adaptation

arXiv:2606.00808v1 Announce Type: new Abstract: Source-free graph domain adaptation (SF-GDA) aims to adapt source-trained graph models to unlabeled target graphs when source graphs are no longer acces

applicationsarxiv-cs-lg

SafeSteer: Localized On-Policy Distillation for Efficient Safety Alignment

arXiv:2606.02530v1 Announce Type: new Abstract: Aligning Large Language Models (LLMs) with human values often degrades their general capabilities, termed the alignment tax. Existing methods mitigate t

Scalar-Measurement Attitude Estimation on mathbf{SO}(3) with Bias Compensation

arXiv:2603.02478v2 Announce Type: replace-cross Abstract: Attitude estimation methods typically rely on full vector measurements from inertial sensors such as accelerometers and magnetometers. This pa

safetyarxiv-cs-ro

Agents

Scaling Behavior of Single LLM-Driven Multi-Agent Systems

arXiv:2606.00655v1 Announce Type: cross Abstract: The burgeoning field of LLM-based Multi-Agent Systems (MAS) promises to tackle complex tasks through collaborative intelligence, yet fundamental quest

agentsarxiv-cs-ai

Agents

// Scaling Behavior of Single LLM-Driven Multi-Agent Systems // Does adding more agents actually make a multi-agent system better? It's poss…

// Scaling Behavior of Single LLM-Driven Multi-Agent Systems // Does adding more agents actually make a multi-agent system better? It's possible that collective intelligence emerges from interaction d

agentsdair-ai--x

Tutorials

SCL: Towards Domain Generalization via Single-Temporal Multimodal Contrastive Learning for Remote Sensing Change Detection

arXiv:2404.11326v5 Announce Type: replace Abstract: In recent years, change detection and anomaly detection models based on CNN and transformer have achieved remarkable success across various datasets

tutorialsarxiv-cs-cv

SECUREVENT: Hybrid AI/ML Security Monitoring for Distributed Event-Based Systems

arXiv:2606.01741v1 Announce Type: cross Abstract: Distributed event-based systems have become a common substrate for Internet-scale publish/subscribe services, IoT telemetry, cloud-native microservice

Self-Healing Agentic Orchestrators for Reliable Tool-Augmented Large Language Model Systems

arXiv:2606.01416v1 Announce Type: new Abstract: Tool-augmented large language model (LLM) agents rely on orchestration layers that coordinate planning, retrieval, tool invocation, validation, memory,

Self-Regulating Annealing in Heavy-Tailed Diffusion Models

arXiv:2606.01645v1 Announce Type: cross Abstract: Diffusion models have emerged as a leading framework for deep generative modeling. While the standard Gaussian formulation is theoretically convenient

SEMBridge: Tagless-Final Program Semantics with Weakest-Precondition and Bounded-Checking Interpretations

arXiv:2606.00220v1 Announce Type: cross Abstract: Formal methods provide rigorous accounts of program behavior, but practical software engineering often works through executable libraries, tests, and

researcharxiv-cs-ai

SentimentLens: Reconciling Sentiment and Ratings via Dual-Modality in the Hospitality Sector

arXiv:2606.00084v1 Announce Type: cross Abstract: Online travel platforms generate vast volumes of user-generated hotel reviews, offering rich opportunities to understand traveler experiences at scale