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pratzohol · Oct 24, 2024 · e81aabf · e81aabf
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diff --git a/docs/Notes/Graph_Neural_Networks/1-icl-over-graphs-GPPT.md b/docs/Notes/Graph_Neural_Networks/1-icl-over-graphs-GPPT.md
@@ -1,8 +1,5 @@
 ---
 title: "Prompting : GPPT"
-tags:
-    - Prompting
-    - Graphs
 ---
 
 # Prompting over Graphs : GPPT
@@ -48,7 +45,7 @@ The orthogonal prompt initialization and regularization are proposed to separate
 
 - **GCC** : Leverages contrastive learning to capture the universal network topological properties across multiple networks.
 - **GPT-GNN** : Introduces a self-supervised attributed graph generation task to pre-train GNN models that can capture the structural and semantic properties of the graph.
--  **L2P-GNN** : Utilizes meta-learning to learn the fine-tune strategy during the pre-training process.
+- **L2P-GNN** : Utilizes meta-learning to learn the fine-tune strategy during the pre-training process.
 
 ## 4. Preliminary Knowledge
 
@@ -198,5 +195,5 @@ $$\mathcal{L_o} = \sum_{m} || E^m (E^m)^T - I ||_F^2$$
 
 [//begin]: # "Autogenerated link references for markdown compatibility"
 [in-context-learning|In-context Learning (ICL)]: ../Miscellaneous/in-context-learning "In-context Learning (ICL)"
-[icl-over-graphs-PRODIGY|ICL : PRODIGY]: icl-over-graphs-prodigy "ICL : PRODIGY"
+[Notes/Graph_Neural_Networks/2-icl-over-graphs-PRODIGY|ICL : PRODIGY]: 2-icl-over-graphs-PRODIGY "ICL : PRODIGY"
 [//end]: # "Autogenerated link references"
diff --git a/docs/Notes/Graph_Neural_Networks/2-icl-over-graphs-PRODIGY.md b/docs/Notes/Graph_Neural_Networks/2-icl-over-graphs-PRODIGY.md
@@ -1,9 +1,5 @@
 ---
 title: "ICL : PRODIGY"
-tags:
-    - Prompting
-    - ICL
-    - Graphs
 ---
 
 # ICL over Graphs : PRODIGY

diff --git a/...tes/Graphs_with_LLMs/1-one-for-all-ofa.md → ...raph_Neural_Networks/3-one-for-all-ofa.md b/...tes/Graphs_with_LLMs/1-one-for-all-ofa.md → ...raph_Neural_Networks/3-one-for-all-ofa.md
@@ -1,10 +1,5 @@
 ---
 title: "OneForAll (OFA)"
-tags:
-    - Prompting
-    - LLMs
-    - Graphs
-    - ICL
 ---
 
 # ICL over Graphs : OFA
@@ -85,6 +80,6 @@ _**NOTE**_ : Definition of [[in-context-learning|In-context Learning (ICL)]] is
 
 
 [//begin]: # "Autogenerated link references for markdown compatibility"
-[icl-over-graphs-prodigy|ICL : PRODIGY]: ../Graph_Neural_Networks/icl-over-graphs-prodigy "ICL : PRODIGY"
+[Notes/Graph_Neural_Networks/2-icl-over-graphs-PRODIGY|ICL : PRODIGY]: ../Graph_Neural_Networks/2-icl-over-graphs-PRODIGY "ICL : PRODIGY"
 [in-context-learning|In-context Learning (ICL)]: ../Miscellaneous/in-context-learning "In-context Learning (ICL)"
 [//end]: # "Autogenerated link references"
diff --git a/docs/Notes/Graphs_with_LLMs/2-talk-like-graph.md b/docs/Notes/Graphs_with_LLMs/2-talk-like-graph.md
diff --git a/docs/Notes/Graphs_with_LLMs/3-potential-llm-graph-learning.md b/docs/Notes/Graphs_with_LLMs/3-potential-llm-graph-learning.md
diff --git a/docs/Notes/Maths/bigoplus.md b/docs/Notes/Maths/bigoplus.md
@@ -1,7 +1,5 @@
 ---
 title: \bigoplus
-tags:
-    - LaTeX
 ---
 
 ## 1. \bigoplus operator

diff --git a/docs/Notes/Miscellaneous/erdos-renyl-model.md b/docs/Notes/Miscellaneous/erdos-renyl-model.md
@@ -1,7 +1,5 @@
 ---
 title: "Erdos Renyl Model"
-tags:
-    - Graphs
 ---
 
 # Erdos Renyl Model : Generating Random Graphs
@@ -19,4 +17,4 @@ tags:
 
 ## 2. References
 
-- https://www.geeksforgeeks.org/erdos-renyl-model-generating-random-graphs/
+- https://www.geeksforgeeks.org/erdos-renyl-model-generating-random-graphs/      
diff --git a/docs/Notes/Miscellaneous/in-context-learning.md b/docs/Notes/Miscellaneous/in-context-learning.md
@@ -1,8 +1,3 @@
----
-tags:
-    - ICL
----
-
 # In-context Learning (ICL)
 
 ## 1. Definition
@@ -25,5 +20,5 @@ In-context Learning or ICL was defined in ["Language Models are few-shot learner
 
 
 [//begin]: # "Autogenerated link references for markdown compatibility"
-[icl-over-graphs-PRODIGY|ICL over Graphs : PRODIGY]: ../Graph_Neural_Networks/icl-over-graphs-PRODIGY "ICL : PRODIGY"
+[Notes/Graph_Neural_Networks/2-icl-over-graphs-PRODIGY|ICL over Graphs : PRODIGY]: ../Graph_Neural_Networks/2-icl-over-graphs-PRODIGY "ICL : PRODIGY"
 [//end]: # "Autogenerated link references"
diff --git a/docs/Notes/Miscellaneous/types-of-learning.md b/docs/Notes/Miscellaneous/types-of-learning.md
@@ -1,8 +1,3 @@
----
-tags:
-    - Basics
----
-
 # Types of Learning
 
 There are broadly 3 different types of learning in Machine Learning paradigm:

diff --git a/docs/Notes/list-of-papers.md b/docs/Notes/list-of-papers.md
@@ -10,8 +10,8 @@ List of all the papers I've covered till date :
 | ----- | ------------- | ------------ |
 | 1. | [GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural Networks](https://dl.acm.org/doi/abs/10.1145/3534678.3539249) | [Click here](./Graph_Neural_Networks/1-icl-over-graphs-GPPT.md) |
 | 2. | [PRODIGY : Enabling In-context learning over graphs](https://arxiv.org/abs/2305.12600) | [Click here](./Graph_Neural_Networks/2-icl-over-graphs-PRODIGY.md) |
-| 3. | [Talk like a Graph : Encoding Graphs for LLMs](https://arxiv.org/pdf/2310.04560.pdf) | [Click here](./Graphs_with_LLMs/2-talk-like-graph.md) |
-| 4. | [ONE FOR ALL: TOWARDS TRAINING ONE GRAPH MODEL FOR ALL CLASSIFICATION TASKS](https://arxiv.org/pdf/2310.00149v1.pdf) | [Click here](./Graphs_with_LLMs/1-one-for-all-ofa.md) |
-| 5. | [Exploring the Potential of LLMs in Learning on Graphs](https://arxiv.org/pdf/2307.03393.pdf) | [Click here](./Graphs_with_LLMs/3-potential-llm-graph-learning.md) |
+| 3. | [Talk like a Graph : Encoding Graphs for LLMs](https://arxiv.org/pdf/2310.04560.pdf) | [Click here](Graph_Neural_Networks/4-talk-like-graph.md) |
+| 4. | [ONE FOR ALL: TOWARDS TRAINING ONE GRAPH MODEL FOR ALL CLASSIFICATION TASKS](https://arxiv.org/pdf/2310.00149v1.pdf) | [Click here](Graph_Neural_Networks/3-one-for-all-ofa.md) |
+| 5. | [Exploring the Potential of LLMs in Learning on Graphs](https://arxiv.org/pdf/2307.03393.pdf) | [Click here](Graph_Neural_Networks/3-potential-llm-graph-learning.md) |
 | 6. | TBA | [Click here]() |
 
diff --git a/docs/Python/quick-pytorch.md b/docs/Python/quick-pytorch.md