Search: “papers”

Random-Set Graph Neural Networks

arXiv:2605.11987v1 Announce Type: cross Abstract: Uncertainty quantification has become an important factor in understanding the data representations produced by Graph Neural Networks (GNNs). Despite

agentsarxiv-cs-lg

Real-Scale Island Area and Coastline Estimation using Only its Place Name or Coordinates

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arXiv:2605.11267v1 Announce Type: new Abstract: Accurate measurement of island area and coastline length is crucial for coastal zone monitoring and oceanographic analysis. However, traditional measure

safetyarxiv-cs-cv

13 May 2026

Real-Time Whole-Body Teleoperation of a Humanoid Robot Using IMU-Based Motion Capture with Sim2Sim and Sim2Real Validation

arXiv:2605.12347v1 Announce Type: new Abstract: Stable, low-latency whole-body teleoperation of humanoid robots is an open research challenge, complicated by kinematic mismatches between human and rob

researcharxiv-cs-ro

Reconsidering the energy efficiency of spiking neural networks

model-releasesarxiv-cs-lg

arXiv:2409.08290v4 Announce Type: replace-cross Abstract: Spiking Neural Networks (SNNs) promise higher energy efficiency over conventional Quantized Artificial Neural Networks (QNNs) due to their eve

Reconstruction of Personally Identifiable Information from Supervised Finetuned Models

arXiv:2605.12264v1 Announce Type: cross Abstract: Supervised Finetuning (SFT) has become one of the primary methods for adapting a large language model (LLM) with extensive pre-trained knowledge to do

applicationsarxiv-cs-cl

Rethinking LLMOps for Fraud and AML: Building a Compliance-Grade LLM Serving Stack

model-releasesarxiv-cs-lg

arXiv:2605.11232v1 Announce Type: cross Abstract: Fraud detection and anti-money-laundering (AML) compliance are high-value domains for large language models (LLMs), but their serving requirements dif

Tutorials

Revisiting Photometric Ambiguity for Accurate Gaussian-Splatting Surface Reconstruction

arXiv:2605.12494v1 Announce Type: new Abstract: Surface reconstruction with differentiable rendering has achieved impressive performance in recent years, yet the pervasive photometric ambiguities have

tutorialsarxiv-cs-cv

Robust Multi-Agent Path Finding under Observation Attacks: A Principled Adversarial-Plus-Smoothing Training Recipe

arXiv:2605.11469v1 Announce Type: new Abstract: Decentralized multi-agent path finding (MAPF) routes a team of agents on a shared grid, each acting from its own local view. The standard solution train

Robust Promptable Video Object Segmentation

arXiv:2605.12006v1 Announce Type: new Abstract: The performance of promptable video object segmentation (PVOS) models substantially degrades under input corruptions, which prevents PVOS deployment in

Robustness Certificates for Neural Networks against Adversarial Attacks

arXiv:2512.20865v2 Announce Type: replace Abstract: The increasing use of machine learning in safety-critical domains amplifies the risk of adversarial threats, especially data poisoning attacks that

Sampling-Based Follow-the-Leader Motion Planning for Manipulator-Mounted Continuum Robots

arXiv:2605.11618v1 Announce Type: new Abstract: Follow-the-leader (FTL) motion exploits the unique morphology of continuum robots (CRs) to navigate confined spaces by having the body retrace the path

researcharxiv-cs-ro

ShapeCodeBench: A Renewable Benchmark for Perception-to-Program Reconstruction of Synthetic Shape Scenes

arXiv:2605.11680v1 Announce Type: new Abstract: We introduce ShapeCodeBench, a synthetic benchmark for perception-to-program reconstruction: given a rendered raster image, a model must emit an executa

Tutorials

Smoothness Errors in Dynamics Models and How to Avoid Them

arXiv:2602.05352v2 Announce Type: replace Abstract: Modern neural networks have shown promise for solving partial differential equations over surfaces, often by discretizing the surface as a mesh and

tutorialsarxiv-cs-lg

SOAR: Regression-based LiDAR Relocalization for UAVs

arXiv:2602.13267v3 Announce Type: replace Abstract: Regression-based LiDAR relocalization has recently emerged as a promising solution for high-precision positioning in GNSS-denied environments. Howev

Sparsity-Constraint Optimization via Splicing Iteration

model-releasesarxiv-cs-lg

arXiv:2406.12017v2 Announce Type: replace-cross Abstract: Sparsity-constrained optimization underlies many problems in signal processing, statistics, and machine learning. State-of-the-art hard-thresh

Spectral-Adaptive Modulation Networks for Visual Perception

arXiv:2503.23947v2 Announce Type: replace Abstract: Recent studies have shown that 2D convolution and self-attention exhibit distinct spectral behaviors, and optimizing their spectral properties can e

safetyarxiv-cs-cv

SyncDPO: Enhancing Temporal Synchronization in Video-Audio Joint Generation via Preference Learning

arXiv:2605.12179v1 Announce Type: new Abstract: Recent advancements in video-audio joint generation have achieved remarkable success in semantic correspondence. However, achieving precise temporal syn

Tackling Fake Forgetting through Uncertainty Quantification

arXiv:2501.19403v3 Announce Type: replace Abstract: Machine unlearning seeks to remove the influence of specified data from a trained model. While the unlearning accuracy provides a widely used metric

TAR: Text Semantic Assisted Cross-modal Image Registration Framework for Optical and SAR Images

arXiv:2605.12064v1 Announce Type: new Abstract: Existing deep learning-based methods can capture shared features from optical and synthetic aperture radar (SAR) images for spatial alignment. However,

safetyarxiv-cs-cv

Towards Order Fairness: Mitigating LLMs Order Sensitivity through Dual Group Advantage Optimization

arXiv:2605.11974v1 Announce Type: new Abstract: Large Language Models (LLMs) suffer from order bias, where their performance is affected by the arrangement order of input elements. This unfairness lim

Toxicity Detection Should Measure Contextual Harm, Not Text-Intrinsic Badness

arXiv:2503.16072v4 Announce Type: replace-cross Abstract: Toxicity detection has become core safety infrastructure for online moderation, dataset filtering, and deployed language-model systems. Yet mo

safetyarxiv-cs-cl

Transferable Delay-Aware Reinforcement Learning via Implicit Causal Graph Modeling

arXiv:2605.12312v1 Announce Type: new Abstract: Random delays weaken the temporal correspondence between actions and subsequent state feedback, making it difficult for agents to identify the true prop

Understanding and Preventing Entropy Collapse in RLVR with On-Policy Entropy Flow Optimization

arXiv:2605.11491v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become an effective paradigm for improving the reasoning ability of large language models. How

UniFixer: A Universal Reference-Guided Fixer for Diffusion-Based View Synthesis

arXiv:2605.12169v1 Announce Type: new Abstract: With the recent surge of generative models, diffusion-based approaches have become mainstream for view synthesis tasks, either in an explicit depth-warp

safetyarxiv-cs-cv

Unlocking Compositional Generalization in Continual Few-Shot Learning

arXiv:2605.11710v1 Announce Type: cross Abstract: Object-centric representations promise a key property for few-shot learning: Rather than treating a scene as a single unit, a model can decompose it i

Unpacking the Eye of the Beholder: Social Location, Identity, and the Moving Target of Political Perspectives

arXiv:2605.11166v1 Announce Type: new Abstract: Political and social identities structure how people evaluate political information, a finding decades deep in political science and routinely discarded

When Looking Is Not Enough: Visual Attention Structure Reveals Hallucination in MLLMs

arXiv:2605.11559v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have become a key interface for visual reasoning and grounded question answering, yet they remain vulnerable to

Why Conclusions Diverge from the Same Observations: Formalizing World-Model Non-Identifiability via an Inference

arXiv:2605.12255v1 Announce Type: cross Abstract: When people share the same documents and observations yet reach different conclusions, the disagreement often shifts into a judgment that the other pa

applicationsarxiv-cs-lg

XWOD: A Real-World Benchmark for Object Detection under Extreme Weather Conditions

arXiv:2605.11521v1 Announce Type: new Abstract: Autonomous driving and intelligent transportation systems remain vulnerable under extreme weather. The U.S. Federal Highway Administration reports that

Zero-shot Human Pose Estimation using Diffusion-based Inverse solvers

arXiv:2510.02043v2 Announce Type: replace Abstract: Pose estimation refers to tracking a human's full body posture, including their head, torso, arms, and legs. The problem is challenging in practical

A Controlled Diagnostic Study of Hardware-Induced Distortions in Hardware-Aware Training

arXiv:2605.09416v1 Announce Type: new Abstract: Hardware-aware training (HAT) is widely used to improve the robustness of neural networks on non-ideal AI accelerators, such as analog in-memory computi

A Cross-Layered Multi-Drone Coordination for Medical Supply Delivery during Disaster Response Management

arXiv:2605.09342v1 Announce Type: cross Abstract: Autonomous drone fleets have immense potential in medical supply delivery during disaster incident response. However, coordinating multiple drones in

A Market-Rule-Informed Neural Network for Efficient Imbalance Electricity Price Forecasting

arXiv:2605.09061v1 Announce Type: cross Abstract: Accurate and efficient imbalance electricity price forecasting is critical for industrial energy trading systems, especially as battery assets and aut

Local Ai

A Physical Theory of Backpropagation: Exact Gradients from the Least-Action Principle

arXiv:2602.02281v2 Announce Type: replace-cross Abstract: Backpropagation is typically presented as a symbolic procedure: a backward pass topologically distinct from inference, with non-local error si

local-aiarxiv-cs-ai

A Prompt-Aware Structuring Framework for Reliable Reuse of AI-Generated Content in the Agentic Web

arXiv:2605.09283v1 Announce Type: new Abstract: The evolution of Large Language Models (LLMs) and the software agents built on them (AI agents) marks a turning point in the transition from a human-cen

agentsarxiv-cs-ai

A Qualitative Test-Risk Mechanism for Scaling Behavior in Normalized Residual Networks

arXiv:2605.08297v1 Announce Type: cross Abstract: The scaling behavior, in which test performance often improves as model size and data increase, is a central empirical phenomenon in modern deep learn

researcharxiv-cs-ai

Local Ai

A Reconfigurable Multiplier Architecture for Error-Resilient Applications in RISC-V Core

arXiv:2605.08785v1 Announce Type: cross Abstract: Neural Networks (NNs) have been widely adopted due to their outstanding efficacy and adaptability across computer vision and deep learning application

local-aiarxiv-cs-ai

A Recursive Decomposition Framework for Causal Structure Learning in the Presence of Latent Variables

arXiv:2605.10651v1 Announce Type: cross Abstract: Constraint-based causal discovery is widely used for learning causal structures, but heavy reliance on conditional independence (CI) testing makes it

applicationsarxiv-cs-ai

A Tale of Two Problems: Multi-Task Bilevel Learning Meets Equality Constrained Multi-Objective Optimization

arXiv:2605.09094v1 Announce Type: new Abstract: In recent years, bilevel optimization (BLO) has attracted significant attention for its broad applications in machine learning. However, most existing w

Absurd World: A Simple Yet Powerful Method to Absurdify the Real-world for Probing LLM Reasoning Capabilities

arXiv:2605.09678v1 Announce Type: new Abstract: While extremely powerful and versatile at various tasks, the thinking capabilities of large language models (LLMs) are often put under scrutiny as they

applicationsarxiv-cs-ai

Active-SAOOD: Active Sparsely Annotated Oriented Object Detection in Remote Sensing Images

arXiv:2605.10162v1 Announce Type: new Abstract: Reducing the annotation cost of oriented object detection in remote sensing remains a major challenge. Recently, sparse annotation has gained attention

applicationsarxiv-cs-cv

Adaptive Action Chunking via Multi-Chunk Q Value Estimation

arXiv:2605.10044v1 Announce Type: cross Abstract: Action chunking emerged as a pivotal technique in imitation learning, enabling policies to predict cohesive action sequences rather than single action

agentsarxiv-cs-ai

Adaptive Data Harvesting for Efficient Neural Network Learning with Universal Constraints

arXiv:2605.09707v1 Announce Type: cross Abstract: Training neural networks to satisfy universal constraints over continuous domains poses unique challenges. Common examples include Lyapunov Neural Net

safetyarxiv-cs-ai

Adaptive Memory Momentum via a Model-Based Framework for Deep Learning Optimization

arXiv:2510.04988v3 Announce Type: replace Abstract: The vast majority of modern deep learning models are trained with momentum-based first-order optimizers. The momentum term governs the optimizer's m

Agent-First Tool API: A Semantic Interface Paradigm for Enterprise AI Agent Systems

arXiv:2605.10555v1 Announce Type: new Abstract: As AI agents transition from research prototypes to enterprise production systems, the tool interfaces they consume remain rooted in human-oriented CRUD

agentsarxiv-cs-ai

Agentic Performance at the Edge: Insights from Benchmarking

model-releasesarxiv-cs-ai

arXiv:2605.10384v1 Announce Type: new Abstract: Agentic artificial intelligence (AI) is a natural fit for Internet of Things (IoT) and edge systems, but edge deployments are often constrained to model

AgentPSO: Evolving Agent Reasoning Skill via Multi-agent Particle Swarm Optimization

model-releasesarxiv-cs-ai

arXiv:2605.08704v1 Announce Type: new Abstract: Multi-agent reasoning has shown promise for improving the problem-solving ability of large language models by allowing multiple agents to explore divers

AgentReview: Exploring Peer Review Dynamics with LLM Agents

arXiv:2406.12708v3 Announce Type: replace Abstract: Peer review is fundamental to the integrity and advancement of scientific publication. Traditional methods of peer review analyses often rely on exp

safetyarxiv-cs-cl