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README.md

@@ -5,11 +5,11 @@ configs:
 - config_name: default
   data_files:
   - split: all_time
-    path: 2025-12-15/sqa_citation_ranking_all_time.parquet
+    path: 2025-12-22/sqa_citation_ranking_all_time.parquet
   - split: last_week
-    path: 2025-12-15/sqa_citation_ranking_last_week.parquet
+    path: 2025-12-22/sqa_citation_ranking_last_week.parquet
   - split: last_month
-    path: 2025-12-15/sqa_citation_ranking_last_month.parquet
+    path: 2025-12-22/sqa_citation_ranking_last_month.parquet
 - config_name: '2025-10-07'
   data_files:
   - split: all_time
@@ -90,6 +90,14 @@ configs:
     path: 2025-12-15/sqa_citation_ranking_last_week.parquet
   - split: last_month
     path: 2025-12-15/sqa_citation_ranking_last_month.parquet
+- config_name: '2025-12-22'
+  data_files:
+  - split: all_time
+    path: 2025-12-22/sqa_citation_ranking_all_time.parquet
+  - split: last_week
+    path: 2025-12-22/sqa_citation_ranking_last_week.parquet
+  - split: last_month
+    path: 2025-12-22/sqa_citation_ranking_last_month.parquet
 ---
 
 
@@ -102,6 +110,7 @@ configs:
 
 
 
+
 ## Dataset Summary
 This dataset tracks which scientific papers are most often cited by [**Asta**](https://asta.ai), an agentic research platform that uses retrieval-augmented generation (RAG) to answer scientific questions. Each record is a paper cited by Asta's _Summarize Literature_ tool, ranked by the number of times the system cited that paper. Across more than 113,000 user queries, we track **4M citations** to over **2M distinct papers**.  By making this data public, we aim to create a transparent, trackable measure of which research most directly powers AI-generated answers—helping ensure that scientific contributions are visible and credited in the AI era.