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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>LLM Explainability - SMILE</title>
<meta name="description" content="Large Language Model Explainability research at SMILE">
<!-- Fonts -->
<link href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Castoro" rel="stylesheet">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.4.0/css/all.min.css">
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<!-- CSS -->
<link rel="stylesheet" href="./static/css/index.css">
<link rel="icon" href="https://raw.githubusercontent.com/koo-ec/xwhy/main/docs/graphics/XWhy_Logo_v1.png">
</head>
<body>
<div class="wrapper">
<!-- Sidebar -->
<header class="sidebar">
<div class="profile">
<a href="index.html">
<img src="https://raw.githubusercontent.com/koo-ec/xwhy/main/docs/graphics/XWhy_Logo_v1.png"
alt="XWhy Logo" class="profile-img">
</a>
<h1 class="site-title"><a href="index.html" style="color: inherit;">XWhy / SMILE</a></h1>
<p class="site-subtitle">Explainable AI Research</p>
</div>
<ul class="nav-links">
<li><a href="index.html#about">About</a></li>
<li><a href="index.html#news">News</a></li>
<li><a href="index.html#publications">Publications</a></li>
<li><a href="index.html#team">Team</a></li>
<li><a href="llm.html" class="active">LLM Explainability</a></li>
<li><a href="geo.html">Geo-SMILE</a></li>
<li><a href="multimodal.html">Multi-modal XAI</a></li>
<li><a href="talks.html">Talks & Videos</a></li>
<li><a href="./PointCloud.html">Point Cloud XAI</a></li>
</ul>
<div class="social-links">
<a href="https://github.com/Dependable-Intelligent-Systems-Lab/xwhy" title="GitHub"><i
class="fab fa-github"></i></a>
<a href="https://arxiv.org/abs/2311.07286" title="arXiv"><i class="ai ai-arxiv"></i></a>
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© 2025 XWhy Project.
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</header>
<!-- Main Content -->
<main class="main-content">
<div class="container">
<h1 class="page-title">LLM Explainability</h1>
<p class="lead">Research into interpreting and explaining Large Language Models.</p>
<section>
<h2>Overview</h2>
<p>
As Large Language Models (LLMs) become more prevalent, understanding their decision-making
processes is crucial. Our research focuses on applying SMILE and other interpretability
techniques to LLMs to ensure safety, fairness, and reliability.
</p>
<p>
<em>(Content to be added)</em>
</p>
</section>
</div>
</main>
</div>
</body>
</html>