<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>LLM4XAI | HERCOLE Lab</title><link>https://hercolelab.netlify.app/tags/llm4xai/</link><atom:link href="https://hercolelab.netlify.app/tags/llm4xai/index.xml" rel="self" type="application/rss+xml"/><description>LLM4XAI</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Thu, 05 Nov 2026 00:00:00 +0000</lastBuildDate><image><url>https://hercolelab.netlify.app/media/icon_hu12080033123456965919.png</url><title>LLM4XAI</title><link>https://hercolelab.netlify.app/tags/llm4xai/</link></image><item><title>Join HERCOLE Lab for two events at CIKM 2026</title><link>https://hercolelab.netlify.app/news/26cikm-double-appointment/</link><pubDate>Thu, 05 Nov 2026 00:00:00 +0000</pubDate><guid>https://hercolelab.netlify.app/news/26cikm-double-appointment/</guid><description>&lt;p>We have two appointments at &lt;strong>CIKM 2026&lt;/strong> in Rome. We hope to see you there!&lt;/p>
&lt;p>&lt;strong>Sunday, November 8, 14:00–18:30 — LLM4XAI workshop.&lt;/strong> We will hold &lt;a href="https://hercolelab.github.io/LLM4XAI/" target="_blank" rel="noopener">LLM4XAI: Generative Models for Explainable AI Narratives&lt;/a> in &lt;strong>Sala del Chiostro&lt;/strong> at Sapienza University of Rome&amp;rsquo;s Faculty of Engineering, San Pietro in Vincoli. The workshop brings together researchers working on reliable, useful natural-language explanations of AI decisions. See the &lt;a href="https://cikm2026.diag.uniroma1.it/program/" target="_blank" rel="noopener">CIKM program&lt;/a> for the venue details.&lt;/p>
&lt;p>&lt;strong>Wednesday, November 11, 14:00–15:30 — Paper poster.&lt;/strong> We will present &lt;strong>&amp;ldquo;Counterfactual Explanations for Hypergraph Neural Networks&amp;rdquo;&lt;/strong> at &lt;strong>poster A140&lt;/strong> during Poster &amp;amp; Demo Session 3 in the poster area at Auditorium Parco della Musica Ennio Morricone. Come discuss how small changes to higher-order relationships can explain a hypergraph neural network&amp;rsquo;s predictions. Read the &lt;a href="https://arxiv.org/abs/2602.04360" target="_blank" rel="noopener">paper&lt;/a> or check the &lt;a href="https://cikm2026.diag.uniroma1.it/program/" target="_blank" rel="noopener">CIKM program&lt;/a> for session details.&lt;/p></description></item></channel></rss>