Update for-students.html

for-students.html

@@ -44,14 +44,14 @@ <h2><a id="open-thesis-topics"></a>Open Thesis Topics</h2>
 <ul> <!-- sorted alphabetically by title -->
     <!--<li data-mentor="christopher schröder">Active Learning for Text Classification</li>-->
     <li data-mentor="maximilian heinrich">Analyzing Factors of Persuasion in an Online Debate Forum</li>
-    <li data-mentor="matti wiegmann">Assessing the Quality of Comparative Review Webpages</li>
+    <!--<li data-mentor="matti wiegmann">Assessing the Quality of Comparative Review Webpages</li> -->
     <!--<li data-mentor="martin potthast">Adversarial Learning of Writing Style Representations</li> [needs additional supervisor]--> 
     <!--<li data-mentor="martin potthast, norbert siegmund, benno stein">Argumentation in Software Engineering</li>--> 
     <!--<li data-mentor="janek bevendorff, magdalena wolska">Authorship Attribution based on Supra-segmental Features</li>-->  
     <!--<li data-mentor="roxanne el baff, khalid al-khatib">Automatic Generation of Persuasive Texts</li>-->  
     <!--<li data-mentor="maik fröbe">Automatic Updates of Relevance Labels for Web Search</li> --> 
     <!--<li data-mentor="sascha bondarenko">Axiomatic Argumentative Web Scale Document Re-ranking</li>--> 
-    <li data-mentor="janek bevendorff">Assessing the Robusness of Retrieval Models to Adversarial Examples. </li>
+    <li data-mentor="janek bevendorff">Assessing the Robusness of Retrieval Models to Adversarial Examples</li>
     <!--<li data-mentor="maik fröbe">Building and Operating a Search Engine for Free With Github Pages as an Enabler for a Diverse Search Ecosystem</li>-->
     <!--<li data-mentor="maik fröbe">Children as Searchers: Improving Web Search for Children</li>-->
     <li data-mentor="janek bevendorff">Constructing and Analyzing a diverse Corpus of AI-generated Text</li>
@@ -71,16 +71,18 @@ <h2><a id="open-thesis-topics"></a>Open Thesis Topics</h2>
     <!--<li data-mentor="benno stein, martin potthast">Information Theory and Authorship</li>--> 
     <li data-mentor="lukas gienapp, harry scells">Jointly Learning Decoupled Bi-Encoder Representations for Retrieval</li>
     <li data-mentor="ferdinand schlatt,harry scells">Lightweight Passage Re-ranking Using Embeddings from Pre-trained Language Models</li>
+    <li data-mentor="matti wiegmann">Mining Documents with Trigger Warnings from the Web and Social Media</li>
     <!--<li data-mentor="maximilian heinrich">Logical Features of Neural Networks</li>-->
     <!--<li data-mentor="maik fröbe, harry scells, christopher akiki">Measuring the Correlation of the Effectivenes of Large Language Models and Retrievability</li>-->
     <!--<li data-mentor="maik fröbe">Multi-Task Learning with IR Axioms</li>-->
     <!--<li data-mentor="nailia mirzakhmedova">Persuasive Argument Generation using Generative Adversarial Networks</li> -->
     <!--<li data-mentor="martin potthast, benno stein, matthias hagen, janek bevendorff">Paraphrasing Operations for Heuristic Author Obfuscation</li>-->
-    <li data-mentor="matti wiegmann">Personalization Strategies for LLMs to reduce Harmful Content Generation</li>
+    <!--<li data-mentor="matti wiegmann">Personalization Strategies for LLMs to reduce Harmful Content Generation</li> -->
     <li data-mentor="maximilian heinrich">Psychological Features for Argumentation</li>
     <!--<li data-mentor="maik fröbe">Query Obfuscation for Dense Retrieval Models</li>-->
     <!--<li data-mentor="marcel gohsen">Question Analytics of Conversational QA-Systems: A Gamified Study</li>-->
     <li data-mentor="janek bevendorff">Rating the Degree of Search Engine Optimization of Websites</li>
+    <li data-mentor="matti wiegmann">Retrieval Augmented Generation for Political Science Question Answering</li>
     <li data-mentor="ferdinand schlatt">Robust Out-of-Domain Re-ranking with Cross-Encoders by Fine-tuning on Heterogeneous Collections</li>
     <li data-mentor="magdalena wolska">Simplifying the language of political argumentation</li>
     <!--<li data-mentor="matthias hagen, sebastian günther">Simulating Search Behavior</li>-->