Search: “models”

Safety-aware Goal-oriented Semantic Sensing, Communication, and Control for Robotics

arXiv:2603.13502v2 Announce Type: replace Abstract: Wirelessly-connected robotic systems empower robots with real-time intelligence by leveraging remote computing resources for decision-making. Howeve

safetyarxiv-cs-ro

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SATTC: Structure-Aware Label-Free Test-Time Calibration for Cross-Subject EEG-to-Image Retrieval

DGX agent

arXiv:2603.20738v2 Announce Type: replace Abstract: Cross-subject EEG-to-image retrieval for visual decoding is challenged by subject shift and hubness in the embedding space, which distort similarity

local-aiarxiv-cs-cv

28 Apr 2026

Self-Abstraction Learning for Effective and Stable Training of Deep Neural Networks

arXiv:2604.24313v1 Announce Type: cross Abstract: Training large-scale deep neural networks effectively and stably is essential for applying deep learning across various fields. However, conventional

Self-Organising Memristive Networks as Physical Learning Systems

arXiv:2509.00747v2 Announce Type: replace-cross Abstract: Learning with physical systems is an emerging paradigm that seeks to harness the intrinsic nonlinear dynamics of physical substrates for learn

agentsarxiv-cs-lg

Self-Supervised Representation Learning via Hyperspherical Density Shaping

arXiv:2604.24498v1 Announce Type: new Abstract: Modern self-supervised representation learning methods often relies on empirical heuristics that are not theoretically grounded. In this study we propos

safetyarxiv-cs-cv

Shape of Memory: a Geometric Analysis of Machine Unlearning in Second-Order Optimizers

arXiv:2604.23046v1 Announce Type: new Abstract: We argue that current definitions of machine unlearning are underspecified for second-order optimizers. We compare first-order and second-order learners

ShowFlow: From Robust Single Concept to Condition-Free Multi-Concept Generation

arXiv:2506.18493v2 Announce Type: replace Abstract: Customizing image generation remains a core challenge in controllable image synthesis. For single-concept generation, maintaining both identity pres

safetyarxiv-cs-cv

SMP: Reusable Score-Matching Motion Priors for Physics-Based Character Control

arXiv:2512.03028v3 Announce Type: replace-cross Abstract: Data-driven motion priors that can guide agents toward producing naturalistic behaviors play a pivotal role in creating life-like virtual char

safetyarxiv-cs-ai

StackFeat RL: Reinforcement Learning over Iterative Dual Criterion Feature Selection for Stable Biomarker Discovery

arXiv:2604.22892v1 Announce Type: new Abstract: Feature selection in high-dimensional genomic data (d gg n) demands methods that are simultaneously accurate, sparse, and stable. Existing approaches ei

safetyarxiv-cs-lg

STAND: Semantic Anchoring Constraint with Dual-Granularity Disambiguation for Remote Sensing Image Change Captioning

arXiv:2604.23309v1 Announce Type: new Abstract: Remote sensing image change captioning (RSICC) aims to describe the difference between two remote sensing images. While recent methods have explored vid

Text Tells the Cost: Predicting and Analyzing Repayment Effort of Self-Admitted Technical Debt

arXiv:2309.06020v3 Announce Type: replace-cross Abstract: Technical debt refers to the consequences of sub-optimal decisions made during software development that prioritize short-term benefits over l

Translate or Simplify First: An Analysis of Cross-lingual Text Simplification in English and French

arXiv:2604.23844v1 Announce Type: new Abstract: Cross-Lingual Text Simplification (CLTS) aims to make content more accessible across languages by simultaneously addressing both linguistic complexity a

researcharxiv-cs-cl

Local Ai

U-ViLAR: Uncertainty-Aware Visual Localization for Autonomous Driving via Differentiable Association and Registration

arXiv:2507.04503v2 Announce Type: replace Abstract: Accurate localization using visual information is a critical yet challenging task, especially in urban environments where nearby buildings and const

local-aiarxiv-cs-cv

UNSEEN: A Cross-Stack LLM Unlearning Defense against AR-LLM Social Engineering Attacks

arXiv:2604.23141v1 Announce Type: cross Abstract: Emerging AR-LLM-based Social Engineering attack (e.g., SEAR) is at the edge of posing great threats to real-world social life. In such AR-LLM-SE attac

safetyarxiv-cs-ai

Unstable Rankings in Bayesian Deep Learning Evaluation

arXiv:2604.23102v1 Announce Type: new Abstract: Standard evaluations of Bayesian deep learning methods assume that metric estimates are reliable, but we show this assumption fails under data scarcity.

Viewport-Unaware Blind Omnidirectional Image Quality Assessment: A Unified and Generalized Approach

arXiv:2604.23953v1 Announce Type: cross Abstract: Blind omnidirectional image quality assessment (BOIQA) presents a great challenge to the visual quality assessment community, due to different storage

Well-Conditioned Oblivious Perturbations in Linear Space

arXiv:2604.23193v1 Announce Type: cross Abstract: Perturbing a deterministic n-dimensional matrix with small Gaussian noise is a cornerstone of smoothed analysis of algorithms [Spielman and Teng, JACM

When AI reviews science: Can we trust the referee?

arXiv:2604.23593v1 Announce Type: new Abstract: The volume of scientific submissions continues to climb, outpacing the capacity of qualified human referees and stretching editorial timelines. At the s

tutorialsarxiv-cs-ai

When Annotators Agree but Labels Disagree: The Projection Problem in Stance Detection

arXiv:2603.24231v2 Announce Type: replace Abstract: Stance detection is nearly always formulated as classifying text into Favor, Against, or Neutral. This convention was inherited from debate analysis

safetyarxiv-cs-cl

When Chain-of-Thought Fails, the Solution Hides in the Hidden States

arXiv:2604.23351v1 Announce Type: cross Abstract: Whether intermediate reasoning is computationally useful or merely explanatory depends on whether chain-of-thought (CoT) tokens contain task-relevant

When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions

arXiv:2604.23528v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) provide a promising machine learning framework for solving partial differential equations, but their training o

Local Ai

3DAlign-DAER: Dynamic Attention Policy and Efficient Retrieval Strategy for Fine-grained 3D-Text Alignment at Scale

arXiv:2511.13211v2 Announce Type: replace Abstract: Despite recent advancements in 3D-text cross-modal alignment, existing state-of-the-art methods still struggle to align fine-grained textual semanti

local-aiarxiv-cs-cv

A general optimization solver based on OP-to-MaxSAT reduction

arXiv:2604.21961v1 Announce Type: cross Abstract: Optimization problems are fundamental in diverse fields, such as engineering, economics, and scientific computing. However, current algorithms are mos

A Probabilistic Framework for Hierarchical Goal Recognition

arXiv:2604.22256v1 Announce Type: cross Abstract: Goal recognition aims to infer an agent's goal from observations of its behaviour. In realistic settings, recognition can benefit from exploiting hier

agentsarxiv-cs-ai

An Integrated Framework for Explainable, Fair, and Observable Hospital Readmission Prediction: Development and Validation on MIMIC-IV

arXiv:2604.22535v1 Announce Type: new Abstract: Objective: To propose and retrospectively validate an integrated framework addressing three barriers to clinical translation of readmission prediction:

safetyarxiv-cs-lg

Assessing the impact of dimensionality reduction on clustering performance -- a systematic study

arXiv:2604.22099v1 Announce Type: new Abstract: Dimensionality reduction is a critical preprocessing step for clustering high-dimensional data, yet comprehensive evaluation of its impact across divers

Audio Video Verbal Analysis (AVVA) for Capturing Classroom Dialogues

arXiv:2604.22043v1 Announce Type: cross Abstract: Background: The classroom discourse analysis has been transformed by the growing use of audio-video multimodal data, which demands analytical methods

CAGE-SGG: Counterfactual Active Graph Evidence for Open-Vocabulary Scene Graph Generation

arXiv:2604.22274v1 Announce Type: new Abstract: Open-vocabulary scene graph generation (SGG) aims to describe visual scenes with flexible and fine-grained relation phrases beyond a fixed predicate voc

Consequentialist Objectives and Catastrophe

arXiv:2603.15017v3 Announce Type: replace Abstract: Because human preferences are too complex to codify, AIs operate with misspecified objectives. Optimizing such objectives often produces undesirable

Applications

Contrastive Semantic Projection: Faithful Neuron Labeling with Contrastive Examples

arXiv:2604.22477v1 Announce Type: new Abstract: Neuron labeling assigns textual descriptions to internal units of deep networks. Existing approaches typically rely on highly activating examples, often

applicationsarxiv-cs-cv

Data-Driven Analysis of AI in Medical Device Software in China: Trends of Deep Learning and Traditional AI Based on Regulatory Data

arXiv:2411.07378v3 Announce Type: replace Abstract: Artificial intelligence (AI) in medical device software (MDSW) represents a transformative clinical technology, attracting increasing attention with

Evolving Thematic Map Design in Academic Cartography: A Thirty-Year Study Based on Multilingual Journals

arXiv:2604.22539v1 Announce Type: new Abstract: Thematic maps play a central role in academic communication, yet their large-scale design evolution has rarely been examined empirically. This study pre

Fast, close, non-singular and property-preserving approximations of entropic measures

arXiv:2505.14234v2 Announce Type: replace-cross Abstract: Entropic measures like Shannon entropy (SE), its quantum mechanical analogue von Neumann entropy, and Kullback-Leibler divergence (KL) are key

Federated Nonlinear System Identification

arXiv:2508.15025v5 Announce Type: replace Abstract: We consider federated learning of linearly-parameterized nonlinear systems. We establish theoretical guarantees on the effectiveness of federated no

GOSPA and T-GOSPA quasi-metrics for evaluation of multi-object tracking algorithms

arXiv:2507.13706v2 Announce Type: replace Abstract: This paper introduces two quasi-metrics for performance assessment of multi-object tracking (MOT) algorithms. One quasi-metric is an extension of th

tutorialsarxiv-cs-cv

Local Ai

How Supply Chain Dependencies Complicate Bias Measurement and Accountability Attribution in AI Hiring Applications

arXiv:2604.22679v1 Announce Type: cross Abstract: The increasing adoption of AI systems in hiring has raised concerns about algorithmic bias and accountability, prompting regulatory responses includin

local-aiarxiv-cs-ai

Applications

Information-Theoretic Geometry Optimization and Physics-Aware Learning for Calibration-Free Magnetic Localization

arXiv:2604.22526v1 Announce Type: new Abstract: Wireless localization of permanent magnets enables occlusion-free guidance for medical interventions, yet its practical accuracy is fundamentally limite

applicationsarxiv-cs-ro

Operational Feature Fingerprints of Graph Datasets via a White-Box Signal-Subspace Probe

arXiv:2604.22676v1 Announce Type: new Abstract: Graph neural networks achieve strong node-classification accuracy, but their learned message passing entangles ego attributes, neighborhood smoothing, h

PASR: Pose-Aware 3D Shape Retrieval from Occluded Single Views

arXiv:2604.22658v1 Announce Type: new Abstract: Single-view 3D shape retrieval is a fundamental yet challenging task that is increasingly important with the growth of available 3D data. Existing appro

tutorialsarxiv-cs-cv

Pliable rejection sampling

arXiv:2604.22385v1 Announce Type: cross Abstract: Rejection sampling is a technique for sampling from difficult distributions. However, its use is limited due to a high rejection rate. Common adaptive

tutorialsarxiv-cs-lg

PoLO: Proof-of-Learning and Proof-of-Ownership at Once with Chained Watermarking

arXiv:2505.12296v2 Announce Type: replace-cross Abstract: Our evaluation shows that PoLO achieves extbf{99%} watermark detection accuracy for ownership verification, while preserving data privacy and

Presenting DiaData for Research on Type 1 Diabetes

arXiv:2508.09160v2 Announce Type: replace Abstract: Type 1 diabetes (T1D) is an autoimmune disorder that leads to the destruction of insulin-producing cells, resulting in insulin deficiency, as to why

Protect the Brain When Treating the Heart: A Convolutional Neural Network for Detecting Emboli

arXiv:2604.22258v1 Announce Type: cross Abstract: Gaseous microemboli (GME) represent a common complication of cardiac structural interventions across both surgical and transcatheter approaches. Trans

QDTraj: Exploration of Diverse Trajectory Primitives for Articulated Objects Robotic Manipulation

arXiv:2604.22551v1 Announce Type: cross Abstract: Thanks to the latest advances in learning and robotics, domestic robots are beginning to enter homes, aiming to execute household chores autonomously.

agentsarxiv-cs-ai

Read the Paper, Write the Code: Agentic Reproduction of Social-Science Results

arXiv:2604.21965v1 Announce Type: new Abstract: Recent work has used LLM agents to reproduce empirical social science results with access to both the data and code. We broaden this scope by asking: Ca

agentsarxiv-cs-ai

ReCast: Recasting Learning Signals for Reinforcement Learning in Generative Recommendation

arXiv:2604.22169v1 Announce Type: cross Abstract: Generic group-based RL assumes that sampled rollout groups are already usable learning signals. We show that this assumption breaks down in sparse-hit

safetyarxiv-cs-ai

ReLIC-SGG: Relation Lattice Completion for Open-Vocabulary Scene Graph Generation

arXiv:2604.22546v1 Announce Type: new Abstract: Open-vocabulary scene graph generation (SGG) aims to describe visual scenes with flexible relation phrases beyond a fixed predicate set. Existing method

Applications

Report for NSF Workshop on AI for Electronic Design Automation

arXiv:2601.14541v4 Announce Type: replace-cross Abstract: This report distills the discussions and recommendations from the NSF Workshop on AI for Electronic Design Automation (EDA), held on December

applicationsarxiv-cs-ai