Search: “privacy”

Designing Social Robots for Social-Cognition Training with Autistic Adults

arXiv:2608.18488v1 Announce Type: cross Abstract: Social robots have been widely explored as tools for autism intervention, yet this literature has focused predominantly on children and has rarely inv

applicationsarxiv-cs-ro

20 Aug 2026

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KA2L: A Knowledge-Aware Active Learning Framework for LLMs

DGX agent

arXiv:2603.17566v2 Announce Type: replace Abstract: Fine-tuning large language models (LLMs) with high-quality knowledge has been shown to enhance their performance effectively. However, there is a pa

researcharxiv-cs-cl

20 Aug 2026

Preference Reasoning under Indeterminacy in Large Language Models

arXiv:2608.18631v1 Announce Type: new Abstract: As large language models evolve into decision-making agents, the ability to reason over preferences becomes fundamental to alignment, coordination, and

20 Aug 2026

Vision-Language Models for Egocentric Video: From Hand-Object Interaction to Embodied AI

arXiv:2608.18671v1 Announce Type: new Abstract: Egocentric video captures activities from the wearer's perspective, providing a direct view of human attention, hand--object interaction, and goal-direc

safetyarxiv-cs-cv

20 Aug 2026

ArguLens: An Open-Source System for Automated Essay Scoring and Label-Aware Feedback Generation

model-releasesarxiv-cs-cl

arXiv:2608.17356v1 Announce Type: new Abstract: Most automated essay scoring (AES) systems output a single holistic score without interpretable evidence and rely on closed APIs that introduce data pri

MemCatalyst: Amplifying Data Auditing on Vision-Language Models via Data Poisoning

arXiv:2608.17722v1 Announce Type: cross Abstract: Vision-Language models (VLMs) achieve outstanding performance largely due to the amount of training data available on the internet. At the same time,

tutorialsarxiv-cs-lg

Reflex-Guard: A Low-Latency Guardrail for LLM Prompt Safety Using Dense Semantic Embeddings

model-releasesarxiv-cs-cl

arXiv:2608.17556v1 Announce Type: cross Abstract: Large Language Models (LLMs) in real-world applications often face the risks of specially crafted prompts designed to bypass the safety controls. Exis

SGHA: Evidence-Grounded Research Problem Discovery with Local Language Models

arXiv:2608.17501v1 Announce Type: new Abstract: Recent efforts toward fully automated AI scientists have demonstrated that language-model agents can generate hypotheses, execute experiments, and draft

Spectral Gradient Orthogonalization Improves Differentially Private Training at Scale

arXiv:2608.17415v1 Announce Type: new Abstract: Differentially private training adds isotropic Gaussian noise to clipped gradients, corrupting every singular direction equally. In vision models, where

safetyarxiv-cs-cv

The 10th AI City Challenge

arXiv:2608.17044v1 Announce Type: cross Abstract: The 10th AI City Challenge, held with ECCV 2026, marks a decade of community benchmarking for intelligent transportation, smart cities, and physical A

What If AI Carried Her Imagination? Black Girls as Creators in an AI Storytelling Weekend Program

arXiv:2608.16896v1 Announce Type: cross Abstract: This paper presents the design and outcomes of a seven-weekend AI storytelling program developed for Black girls aged 10-12. Grounded in Afrofuturism

A Responsible Artificial Intelligence Framework for Groundwater Modeling

arXiv:2608.15657v1 Announce Type: new Abstract: The rapid development and widespread application of artificial intelligence (AI) have sparked intense discussions on how to deploy responsible AI system

Coarse-to-Fine Multi-Resolution Diffusion Models for Trajectory Generation in Urban Systems

arXiv:2608.14570v1 Announce Type: new Abstract: Understanding human mobility is critical for a wide range of urban applications, including traffic management, epidemic control, and urban planning. How

Comprehensive language-image pre-training for 3D medical image understanding

arXiv:2510.15042v3 Announce Type: replace Abstract: In the 3D medical image domain, vision-language pre-training is used to create vision-language encoders (VLEs) that can support radiologists by retr

researcharxiv-cs-cv

Computationally tractable robust differentially private mean estimation

arXiv:2606.12654v2 Announce Type: replace-cross Abstract: We develop a new, differentially private mean estimator called the balloon mean. The main features of the balloon mean are that it is computat

Domain Agnostic Text Redaction from Natural Language Rules using Instruction Tuning

arXiv:2608.14693v1 Announce Type: cross Abstract: With the increasing digitization of personal and corporate communication, the automatic sanitization of textual data has become a crucial component of

tutorialsarxiv-cs-ai

FedADB: Class Anchor-Driven Dual-Branch Federated Learning for Mitigating Forgetting

arXiv:2608.15310v1 Announce Type: cross Abstract: Multimodal data collected by heterogeneous devices are used for collaborative training, where federated learning (FL) serves as a key paradigm for eff

safetyarxiv-cs-lg

Federated Self-Supervised Modulation Classification under Non-IID and Imbalanced Data

arXiv:2510.04927v2 Announce Type: replace-cross Abstract: Automatic modulation classification (AMC) is a core enabler of cognitive wireless systems, providing spectrum awareness and supporting adaptiv

applicationsarxiv-cs-ai

FollowUpBot: An LLM-Based Conversational Robot for Automatic Postoperative Follow-up

arXiv:2507.15502v1 Announce Type: cross Abstract: Postoperative follow-up plays a crucial role in monitoring recovery and identifying complications. However, traditional approaches, typically involvin

applicationsarxiv-cs-cl

Generation of Synthetic Fingerphotos with GANs

arXiv:2608.15029v1 Announce Type: new Abstract: Contactless fingerprinting is an emerging approach to biometric authentication that allows users to scan their fingerprints without touching a scanner.

researcharxiv-cs-cv

Identifying Harm in Personalized, Generative AI Systems Requires User-Centered Auditing at the Interaction Level

arXiv:2608.14692v1 Announce Type: cross Abstract: Personalized, generative AI systems increasingly adapt their behavior to individual users over time, fundamentally changing model behavior. While exis

tutorialsarxiv-cs-ai

LUNG-KGMM: Knowledge-Guided Multimodal Learning for Lung Cancer Incidence Prediction

arXiv:2608.14657v1 Announce Type: cross Abstract: Early identification of lung cancer risk is critical for timely intervention, yet existing prediction models are limited by their reliance on single d

applicationsarxiv-cs-cv

Position: AI Governance Needs ISO-like Interoperability Protocols, Not Just Laws

arXiv:2608.14568v1 Announce Type: new Abstract: As Artificial Intelligence (AI) systems become deeply integrated into critical global infrastructure, the urgency for robust governance frameworks has i

SMA: Who Said That? Auditing Membership Leakage in Semi-Black-box RAG Controlling

arXiv:2508.09105v3 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) and its Multimodal Retrieval-Augmented Generation (MRAG) significantly improve the knowledge coverage and conte

Towards Zero-Shot Domain Generalization for ID Cards Presentation Attack Detection

model-releasesarxiv-cs-cv

arXiv:2608.16591v1 Announce Type: new Abstract: Presentation-Attack Detection (PAD) for national ID cards is limited by the lack of publicly available genuine samples, making it difficult for systems

UniFed-VLM: Federated Instruction Tuning for Vision-Language Models with Multiple Heterogeneity

model-releasesarxiv-cs-lg

arXiv:2608.15516v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have demonstrated strong performance in multimodal understanding and generation. However, fine-tuning of VLMs typically re

Designing Sustainable Federated Learning as a Service using Neural Architecture Search

arXiv:2608.14359v1 Announce Type: new Abstract: The sustainability constraints of FLaaS consumers pose significant challenges to maintaining carbon-feasible federated training in FLaaS environments. T

applicationsarxiv-cs-ai

17 Aug 2026

AnchorSIPS: A Synthetic Dataset and Evaluation Resource for Evidence-Supported Psychosis-Risk Symptom Measurement

arXiv:2608.12329v1 Announce Type: cross Abstract: Progress on AI for psychosis-risk assessment is limited by a data-access bottleneck. Real clinical interviews are difficult to share because of privac

14 Aug 2026

Automated Design Optimization via Strategic Search with Large Language Models

arXiv:2511.22651v2 Announce Type: replace-cross Abstract: Optimization methods have long advanced many fields, yet they struggle when faced with design problems where the search space and design param

14 Aug 2026

Heterogeneity-Aware Belief Synchronization for Semantic Communication in AI-Native 6G Networks

arXiv:2608.13394v1 Announce Type: cross Abstract: 6G networks will not be serving as communication infrastructures only; rather, they are expected to evolve into intelligent systems, where thousands o

14 Aug 2026

Benchmarking Trustworthiness of SLMs: Pre-trained vs. Compressed

arXiv:2608.11981v1 Announce Type: new Abstract: Small Language Models (SLMs) have emerged as a more efficient alternative to traditional Large Language Models (LLMs), offering promising potential in r

safetyarxiv-cs-cl

13 Aug 2026

Ethics Practices in AI Development: An Empirical Study Across Roles and Regions

arXiv:2508.09219v3 Announce Type: replace-cross Abstract: Recent advances in AI applications have raised growing concerns about the need for ethical guidelines and regulations to mitigate the risks po

13 Aug 2026

How Organizations Use AI: Evidence from ChatGPT

arXiv:2608.12236v1 Announce Type: cross Abstract: We study how organizations use frontier generative AI by linking ChatGPT Enterprise account records to usage, worker roles, task classifications, and

tutorialsarxiv-cs-ai

13 Aug 2026

Bayesian Federated Cause-of-Death Classification and Quantification Under Distribution Shift

arXiv:2505.02257v2 Announce Type: replace-cross Abstract: In regions lacking medically certified causes of death, verbal autopsy (VA) is a widely used tool to ascertain the cause of death through inte

applicationsarxiv-cs-lg

ConVAWG: A Retrieval-Grounded Framework for Controlled Synthetic Dialogue Generation in Violence Against Women and Girls

arXiv:2608.11200v1 Announce Type: cross Abstract: Synthetic dialogue generation offers a way to study conversational dynamics in sensitive domains where real data are difficult to access, release, or

applicationsarxiv-cs-ai

Edge Phoneme Recognition for Children's Speech through Age-Aware Training

arXiv:2608.10206v1 Announce Type: new Abstract: Detecting phonemes from children's speech has historically been difficult due to the scarcity of training data, and unique characteristics of children's

FedCGR: Federated Cross-Domain Generative Recommendation

arXiv:2608.10929v1 Announce Type: new Abstract: Cross-domain recommendation (CDR) transfers preference knowledge across related domains, but federated deployment makes cross-domain alignment difficult

Knowledge-Guided 3D CT Generation: A Conditioning-Centric Taxonomy

arXiv:2608.09992v1 Announce Type: cross Abstract: Controllable generation guided by external knowledge is a key requirement in modern generative deep learning applications, enabling the synthesis of s

PEAK: Precise and Persistent Concept Erasure via k-Sparse Autoencoders

model-releasesarxiv-cs-cv

arXiv:2608.10985v1 Announce Type: new Abstract: Erasing concepts from large-scale text-to-image (T2I) diffusion models has become increasingly crucial due to the growing concerns over copyright infrin

Situation Graph Prediction for User Perspective Modeling

arXiv:2602.13319v2 Announce Type: replace Abstract: Perspective-aware AI requires modeling evolving internal states---goals, emotions, contexts---not merely preferences. Progress is limited by a data

Smooth Flow Matching for Synthesizing Functional Data

arXiv:2508.13831v4 Announce Type: replace-cross Abstract: Functional data, i.e., random functions observed over a continuous domain, are increasingly available in areas such as biomedical research, he

SQuaT: Self-Supervised Knowledge Distillation via Student-Aware Quantized Teacher Features

arXiv:2608.10709v1 Announce Type: new Abstract: Quantization-Aware Training (QAT) enables the deployment of quantized models with minimal accuracy degradation. However, in practical scenarios, trainin

UserToolBench: A User-Profile-Hidden Benchmark for Personalized Decision Making in Tool-Use LLMs

arXiv:2608.10042v1 Announce Type: cross Abstract: Tool-use LLMs are increasingly asked to act on users' behalf, but existing benchmarks usually focus on profile recall, style imitation, generic tool u

AquiLLM: An Architecture for Supporting Tacit Knowledge Capture in Research Groups

arXiv:2608.08883v1 Announce Type: new Abstract: Recent advances in retrieval-augmented generation (RAG) and large language models (LLMs) enable researchers to integrate AI into scientific workflows. H

Data collection from highways: a geometric, class-agnostic approach to embedded vehicle counting

arXiv:2608.07643v1 Announce Type: new Abstract: Traffic data collection is dominated today by deep object detectors followed by tracking-by-detection, a pipeline that presupposes what is often missing

researcharxiv-cs-cv

DoRF++: Spherical Representation Learning over Doppler Radiance Fields for Robust Wi-Fi Sensing

arXiv:2608.08381v1 Announce Type: new Abstract: Motivated by the IEEE 802.11bf effort to standardize advanced WLAN sensing, interest in Wi-Fi Channel State Information (CSI) for passive, device-free,

applicationsarxiv-cs-cv

Efficient Cross-View Localization in 6G Space-Air-Ground Integrated Network

arXiv:2603.11398v2 Announce Type: replace-cross Abstract: Recently, visual localization has become an important supplement to improve localization reliability, and cross-view approaches can greatly en

Label-Free Parkinson's Disease Screening from Face and Voice through Mechanistic Interpretability

model-releasesarxiv-cs-lg

arXiv:2608.08976v1 Announce Type: new Abstract: Parkinson's disease (PD) is the second most common neurodegenerative disorder. Typical machine learning screening methods require PD labels, but the ava