diff --git a/pages/papers.en.mdx b/pages/papers.en.mdx
index df1cfea..fa085d4 100644
--- a/pages/papers.en.mdx
+++ b/pages/papers.en.mdx
@@ -1,6 +1,6 @@
 # Papers
 
-The following are the latest papers (sorted by release date) on prompt engineering. We update this on a daily basis and new papers come in. We incorporate summaries of these papers to the guides above every week.
+The following are the latest papers (sorted by release date) on prompt engineering for large language models (LLMs). We update the list of papers on a daily/weekly basis.
 
 ## Overviews
 
@@ -20,8 +20,6 @@ The following are the latest papers (sorted by release date) on prompt engineeri
 
 ## Approaches
 
-  - []() (May 2023)
-  - []() (May 2023)
   - [Self-Critique Prompting with Large Language Models for Inductive Instructions](https://arxiv.org/abs/2305.13733) (May 2023)
   - [Better Zero-Shot Reasoning with Self-Adaptive Prompting](https://arxiv.org/abs/2305.14106) (May 2023)
   - [Hierarchical Prompting Assists Large Language Model on Web Navigation](https://arxiv.org/abs/2305.14257) (May 2023)
@@ -204,7 +202,7 @@ The following are the latest papers (sorted by release date) on prompt engineeri
   - [Enhancing Small Medical Learners with Privacy-preserving Contextual Prompting](https://arxiv.org/abs/2305.12723) (May 2023)
   - [Fact-Checking Complex Claims with Program-Guided Reasoning](https://arxiv.org/abs/2305.12744) (May 2023)
   - [A Benchmark on Extremely Weakly Supervised Text Classification: Reconcile Seed Matching and Prompting Approaches](https://arxiv.org/abs/2305.12749) (May 2023)
-  - [This Prompt is Measuring <MASK>: Evaluating Bias Evaluation in Language Models](https://arxiv.org/abs/2305.12757) (May 2023)
+  - [This Prompt is Measuring \<MASK\>: Evaluating Bias Evaluation in Language Models](https://arxiv.org/abs/2305.12757) (May 2023)
   - [Enhancing Cross-lingual Natural Language Inference by Soft Prompting with Multilingual Verbalizer](https://arxiv.org/abs/2305.12761) (May 2023)
   - [Evaluating Prompt-based Question Answering for Object Prediction in the Open Research Knowledge Graph](https://arxiv.org/abs/2305.12900) (May 2023)
   - [Explaining How Transformers Use Context to Build Predictions](https://arxiv.org/abs/2305.12535) (May 2023)