#xai

5 curated events

papersTODAY 04:00 UTC

arXiv Paper Proposes Method for Diversified Counterfactual Explanations

A new arXiv preprint describes an approach for generating counterfactual examples that are both varied and human-interpretable, drawing on expert knowledge to guide the search. Counterfactual examples are a common technique in explainable AI, since they show the smallest input changes that would flip a model's prediction. The work aims to address the limited diversity typical of existing methods while keeping the resulting explanations understandable.

explainability/xai/counterfactuals/research

papersTODAY 04:00 UTC

Study Compares Subjective, Objective, and Mathematical Measures for XAI Evaluation

A new arXiv paper examines how explainable AI methods are assessed, grouping evaluation approaches into subjective measures such as user trust questionnaires, objective measures based on task performance, and mathematical metrics. The authors analyze whether these three families of evaluation strategies produce consistent conclusions by testing them with saliency maps. The work aims to clarify where the different measurement types agree or diverge.

explainability/xai/evaluation/saliency-maps

papersSEP 10 04:00 UTC

XAI-Arena: Testing whether LLMs can judge the quality of explainable AI explanations

A new arXiv paper introduces XAI-Arena, a study of whether large language models can reliably evaluate explanations produced by explainable AI methods. The authors note that current evaluation relies heavily on subjective human judgment, which hurts reproducibility, scalability, and comparability across studies. The work explores automated, LLM-based assessment as a potential alternative to manual expert reviews.

xai/llms/evaluation/benchmark

papersSEP 12 04:00 UTC

X-RACE: Explainable Attribution Method for LSTM-Based Channel Estimation

A new arXiv preprint introduces X-RACE, a method that applies explainable AI attribution techniques to recurrent neural networks, specifically LSTMs, used for channel estimation in high-mobility vehicular settings. The approach aims to address the limited interpretability and computational overhead that hinder trust in deep learning models for this task.

xai/lstm/channel-estimation/research

productsSEP 10 10:00 UTC

Clearview AI tests prototype that gathers personal data using xAI's Grok

Clearview AI has been testing an unreported prototype called InquiryIQ that uses a model from xAI, the maker of Grok, to compile information about individuals. The tool is designed to help law enforcement surface associates, social media accounts, and other details about people identified through Clearview's facial recognition. The reported testing raises fresh privacy concerns about AI-driven surveillance and data aggregation by police.

surveillance/privacy/law-enforcement/xai