Add task categories and improve dataset card

README.md

@@ -1,7 +1,15 @@
 ---
 license: other
+size_categories:
+- 10K<n<100K
+task_categories:
+- text-generation
 license_name: mixed-license
 license_link: LICENSE.md
+tags:
+- llm-agents
+- deployment-time-learning
+- continual-learning
 configs:
 - config_name: alfworld
   data_files: alfworld/alfworld.jsonl
@@ -29,8 +37,6 @@ configs:
   data_files: 2wiki/2wiki.jsonl
 - config_name: ehr
   data_files: ehr/ehr.jsonl
-size_categories:
-- 10K<n<100K
 ---
 
 # DTLBench
@@ -49,6 +55,7 @@ size_categories:
 
 DTLBench is a benchmark for **deployment-time learning** of large language model agents. It collects diverse task streams spanning medical diagnosis, legal analysis, operational reasoning, financial prediction, text-to-SQL, embodied decision making, tabular reasoning on EHRs, deep search, etc.
 
+The dataset was introduced in the paper: [CASCADE: Case-Based Continual Adaptation for Large Language Models During Deployment](https://arxiv.org/abs/2605.06702).
 
 ## Benchmark Overview
 
@@ -134,5 +141,4 @@ If you use DTLBench, please consider citing our paper:
       primaryClass={cs.AI},
       url={https://arxiv.org/abs/2605.06702}, 
 }
-```
-
+```