update!

Author: kargaranamir

.DS_Store

@@ -1,4 +1,6 @@
 _site/
 .jekyll-cache/
 .DS_Store
-.DS_Store
+._.DS_Store
+**/.DS_Store
+**/._.DS_Store

.gitignore

@@ -17,9 +17,9 @@
 		<li><a href="{{ site.url }}{{ site.baseurl }}/publications">Publications</a></li>
 		<!-- <li><a href="{{ site.url }}{{ site.baseurl }}/research">Research</a></li> -->
 		<li><a href="{{ site.url }}{{ site.baseurl }}/projects">Projects</a></li>
-		<li><a href="{{ site.url }}{{ site.baseurl }}/vacancies">Join Us!</a></li>
+		<li><a href="{{ site.url }}{{ site.baseurl }}/vacancies">Open Positions</a></li>
 		<!-- <li><a href="{{ site.url }}{{ site.baseurl }}/blog">Blog</a></li> -->
-		<li><a href="{{ site.url }}{{ site.baseurl }}/about">About Hinrich</a></li>
+		<li><a href="{{ site.url }}{{ site.baseurl }}/about">About Lab Director</a></li>
 		<!-- <li><a href="{{ site.url }}{{ site.baseurl }}/pictures">(Pics)</a></li> -->
 	  </ul>
 	</div>

_data/.DS_Store

@@ -7,7 +7,11 @@ permalink: /about/
 ---
 
 <!-- ![]({{ site.url }}{{ site.baseurl }}/images/teampic/schuetze_citations.jpg){: style="width: 80%; float: center; margin: 20px"} -->
-# CV 
+# Hinrich Schütze CV 
+
+**Wikipedia**: [Link](https://de.wikipedia.org/wiki/Hinrich_Sch%C3%BCtze)
+
+**Google Scholar Profile**: [Link](https://scholar.google.com/citations?hl=en&user=qIL9dWUAAAAJ)
 
 **2021**
 Ellis [Fellow](https://ellis.eu/fellows)
@@ -49,17 +53,6 @@ Xerox Palo Alto Research Center
 
 **1995** PhD in Computational Linguistics, Stanford
 
-### Wikipedia article : [Hinrich Schütze](https://de.wikipedia.org/wiki/Hinrich_Sch%C3%BCtze)
-### Google Scholar Profile (as of 1 Sep 2022)
-
-[Profile link](https://scholar.google.com/citations?hl=en&user=qIL9dWUAAAAJ)
-
-Total Citations : 64,455
-
-h-index	        : 69	
-
-i10-index       : 249
-
-<figure align="center">
+<!-- <figure align="center">
 <img src="{{ site.url }}{{ site.baseurl }}/images/teampic/schuetze_citations_updated.jpg" width="65%" style="padding:16px">
-</figure>
+</figure> -->

_includes/.DS_Store

@@ -6,11 +6,16 @@ sitemap: false
 permalink: /
 ---
 
-We are a dynamic research group at the [Center for Information and Language Processing](https://www.cis.uni-muenchen.de/) located at [Ludwig Maximilian University Munich](https://www.en.uni-muenchen.de/index.html). Our primary focus is linguistically-informed Neural NLP: We use our deep understanding of language in our research and believe in the principle that learning is key to successful NLP -- the same way that the language capabilities of humans are based on learning. 
+We are a dynamic research group at the [Center for Information and Language Processing](https://www.cis.uni-muenchen.de/) at [Ludwig Maximilian University Munich](https://www.en.uni-muenchen.de/index.html), under the supervision of [Prof. Hinrich Schütze](https://www.cis.lmu.de/schuetze/). Our research areas include:
 
-Our research areas are representation learning, multilinguality, machine learning for low-resource scenarios, cognitively motivated deep learning, linguistically informed deep learning (especially for morphology), digital humanities, and the intersection of NLP and robotics.
+- Large Language Models (LLMs): We explore the behavior, structure, and potential of large-scale language models, examining their capabilities, biases, and self-assessment mechanisms to improve reliability and interpretability.
+- Knowledge Expansion in NLP Models: We investigate how models can acquire and integrate new knowledge over time, using techniques that help improve their comprehension and generation abilities.
+- Representation Learning:  We study how language models represent linguistic and conceptual information by analyzing neurons and internal circuits to better understand and refine model behavior.
+- Multilingual NLP: We address challenges in processing and evaluating multiple languages by developing benchmarks and methods for multilingual evaluation, including work on low-resource and non-standard languages.
+- Intersection of NLP and Robotics:  We integrate language understanding into robotic systems to enable natural, adaptable interaction in multimodal environments.
+
+You can find resources (data, code, repositories) released by CIS lab members on our [GitHub page](https://github.com/cisnlp) and [HuggingFace page](https://huggingface.co/cis-lmu). 
 
-You can find resources (data, code, repositories) released by CIS lab members on our [GitHub page](https://github.com/cisnlp) and [HuggingFace page](https://huggingface.co/cis-lmu).
 
 <div markdown="0" id="carousel" class="carousel slide" data-ride="carousel" data-interval="5000" data-pause="hover" >
     <!-- Menu -->
@@ -31,22 +36,22 @@ You can find resources (data, code, repositories) released by CIS lab members on
             <img src="{{ site.url }}{{ site.baseurl }}/images/carousel/cis-group-m.jpg" alt="Slide 1" style="height: 300px"/>
         </div>
         <div class="item">
-            <img src="{{ site.url }}{{ site.baseurl }}/images/carousel/silvia.png" alt="Slide 2" />
+            <img src="{{ site.url }}{{ site.baseurl }}/images/carousel/ofa.png" alt="Slide 2" />
         </div>
         <div class="item">
-            <img src="{{ site.url }}{{ site.baseurl }}/images/carousel/exclique2.jpg" alt="Slide 3" />
+            <img src="{{ site.url }}{{ site.baseurl }}/images/carousel/nolima.jpeg" alt="Slide 3" />
         </div>
         <div class="item">
-            <img src="{{ site.url }}{{ site.baseurl }}/images/carousel/pcasample.jpg" alt="Slide 4" />
+            <img src="{{ site.url }}{{ site.baseurl }}/images/carousel/logitlens.png" alt="Slide 4" />
         </div>
         <div class="item">
-            <img src="{{ site.url }}{{ site.baseurl }}/images/carousel/curve0.jpg" alt="Slide 5" />
+            <img src="{{ site.url }}{{ site.baseurl }}/images/carousel/transmi.jpeg" alt="Slide 5" />
         </div>
         <!-- <div class="item">
-            <img src="{{ site.url }}{{ site.baseurl }}/images/carousel/SmartTipSide.jpg" alt="Slide 6" />
+            <img src="{{ site.url }}{{ site.baseurl }}/images/carousel/memllm.jpeg" alt="Slide 6" />
         </div>       
          <div class="item">
-            <img src="{{ site.url }}{{ site.baseurl }}/images/carousel/lab.jpg" alt="Slide 7" />
+            <img src="{{ site.url }}{{ site.baseurl }}/images/carousel/learn-it-or-leave-it.jpeg" alt="Slide 7" />
         </div> -->
     </div>
   <a class="left carousel-control" href="#carousel" role="button" data-slide="prev">
@@ -73,14 +78,13 @@ Our group publishes extensively in top NLP/ML conferences. Here is the summary o
 | 2019 	|  4  	|   2   	|   3  	|    -   	|     1     	|    5   	|   14  	|
 | 2018 	|  4  	|   3   	|   1  	|    -   	|     -     	|    5   	|   13  	|
  -->
- **We are looking for passionate new PhD students, Postdocs, interns, IDP (TUM) and MSc/BSc thesis students to join the team** [(more info)]({{ site.url }}{{ site.baseurl }}/vacancies) **!**
 
 
-We are grateful for funding from the Munich Centre for Machine Learning ([MCML](https://mcml.ai/)), Elitenetzwerk Bayern (International Doctorate Program), Deutsche Forschungsgemeinschaft ([DFG](https://www.dfg.de/en/)) and from the European Research Council [ERC advanced grant](https://erc.europa.eu/funding/advanced-grants).
+We are grateful for funding from the Munich Center for Machine Learning ([MCML](https://mcml.ai/)), the Elitenetzwerk Bayern (International Doctorate Program), the Deutsche Forschungsgemeinschaft ([DFG](https://www.dfg.de/en/)), and the European Research Council ([ERC Advanced Grant](https://erc.europa.eu/funding/advanced-grants)).
 
 <figure class="fourth">
-  <img src="{{ site.url }}{{ site.baseurl }}/images/logopic/Logo_LMU.png" style="width: 150px"> 
-  <img src="{{ site.url }}{{ site.baseurl }}/images/logopic/Logo_DFG.jpg" style="width: 150px"> 
-  <img src="{{ site.url }}{{ site.baseurl }}/images/logopic/Logo_MCML.png" style="width: 150px"> 
-  <img src="{{ site.url }}{{ site.baseurl }}/images/logopic/Logo_ERC.jpg" style="width: 150px">
+  <img src="{{ site.url }}{{ site.baseurl }}/images/logopic/Logo_LMU.png" style="height: 50px"> 
+  <img src="{{ site.url }}{{ site.baseurl }}/images/logopic/Logo_DFG.jpg" style="height: 50px"> 
+  <img src="{{ site.url }}{{ site.baseurl }}/images/logopic/Logo_MCML.jpg" style="height: 50px"> 
+  <img src="{{ site.url }}{{ site.baseurl }}/images/logopic/Logo_ERC.png" style="height: 50px">
 </figure>

_includes/header.html

@@ -8,9 +8,7 @@ permalink: /vacancies/
 
 # Working at Schütze Lab
 
-We are always looking for new group members with passion, talent, and grit!
-
-You will have the chance to work at the cutting edge of research in computational linguistics and NLP. You may be exploring multilinguality on a Bible corpus of 1700+ languages, improving and enhancing latest transformer models or pushing the state of art on existing NLP tasks; you will be involved in asking the interesting questions, designing algorithms, conducting experiments and finally presenting your research in the best conferences around the world. 
+We are always looking for new group members with passion, talent, and grit! You will have the chance to work at the cutting edge of research in computational linguistics and NLP.  
 
 ### Current open thesis positions
 

_pages/.DS_Store

@@ -6,30 +6,28 @@ sitemap: false
 permalink: /projects/
 ---
 
-# Funded Projects
+# Projects
 
-Our primary focus is linguistically-informed Neural Natural Language Processing (NNLP). Towards that end, we are working on various funded projects, as described below. 
+Our primary focus is linguistically-informed Neural Natural Language Processing. Towards that end, we are working on various funded projects, as described below. 
 
-## ERC Advanced Grant NonSequeToR
+### ERC Advanced Grant NonSequeToR
 
 Text understanding can fundamentally be viewed as a process of composition: the meaning of smaller units is composed to compute the meaning of larger units and eventually of sentences and documents. Our hypothesis is that optimal generalization in deep learning requires that more regular processes of composition are learned as composition functions whereas units that are the output of less regular processes are learned as static embeddings.  We investigate novel representation learning algorithms and architectures to test this hypothesis. The envisioned goal of the project is a new robust and powerful text representation that
 captures all aspects of form and meaning that NLP needs for successful processing of text.
+See more details on [European Commission website](https://cordis.europa.eu/project/id/740516).
 
-([Project Description](https://cordis.europa.eu/project/id/740516))
 <!-- ![]({{ site.url }}{{ site.baseurl }}/images/respic/SpinFluc.png){: style="width: 80%; float: center; margin: 10px"} -->
-## High quality subword vocabulary induction (Project within the Munich Center for Machine Learning)
+### High quality subword vocabulary induction (Project within the Munich Center for Machine Learning)
 
 A common approach in representing text as input for deep learning models is to use heuristically induced word pieces. Such a representation is easier to process than characters, but does not incur the high cost of large word vocabularies. In this project, we will investigate alternatives to currently used heuristics that are a more natural representation of the semantics of text.
+See more details on [MCML website](https://mcml.ai/areas_of_competence/).
 
-([Project Description](https://mcml.ai/areas_of_competence/))
-
-## ReMLAV: Relational Machine Learning for Argument Validation (DFG project)
+### ReMLAV: Relational Machine Learning for Argument Validation (DFG project)
 
 Argument validation is the task of classifying a given argument as valid or invalid based on its linguistic form, the larger document context, world knowledge and other factors. This project aims to combine representation learning (both static and contextualized embeddings) and relational machine learning to solve this task.
+See more details on [DFG website](https://gepris.dfg.de/gepris/projekt/376183703).
 
-([Project Description](https://gepris.dfg.de/gepris/projekt/376183703))
-
-## Munich Doctoral Program (IDK): Premodern Cultures, Global Perspectives and the Foundations of a New Philology
+### Munich Doctoral Program (IDK): Premodern Cultures, Global Perspectives and the Foundations of a New Philology
 Based on an examination of 4000 years of history of literature, this program's goal is to synthesize theory and
 practice of European traditions with those of the East Asian and South Asian cultural spheres as well as the Jewish and
 Arab worlds. A particular focus will be on digital humanities methods.
@@ -38,11 +36,10 @@ Arab worlds. A particular focus will be on digital humanities methods.
 
 <!-- ## ... and more. -->
 
-# Robotics Projects
-As large language models (LLMs) show impressive emergent abilities in various fields, we are exploring multiple directions combining LLMs into robotics.
-Currently, we are mostly interested in the following topics:
 
-## Long-Horizon Language-Conditioned Robotic Manipulation
+### Long-Horizon Language-Conditioned Robotic Manipulation
+
+As large language models (LLMs) show impressive emergent abilities in various fields, we are exploring multiple directions combining LLMs into robotics.
 Given a high-level human instruction, the robot is supposed to understand the language instruction well and perform long-horizon memorizing and complex reasoning to complete the designated task.   
 We open-sourced a challenging benchmark *LoHoRavens* for this task and provided two baselines. 
 See more details on [LoHoRavens page](https://cisnlp.github.io/lohoravens-webpage/).