update readme

README.md

@@ -1,7 +1,7 @@
 ---
 license: other
 license_name: mixed-license
-license_link: LICENSE
+license_link: LICENSE.md
 configs:
 - config_name: alfworld
   data_files: alfworld/alfworld.jsonl
@@ -31,4 +31,85 @@ configs:
   data_files: ehr/ehr.jsonl
 size_categories:
 - 10K<n<100K
----
+---
+
+# DTLBench
+
+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 benchmark is used by **CASCADE**, whose codebase is released at [GitHub Repo](https://github.com/guosyjlu/CASCADE).
+
+## Benchmark Overview
+
+- Total tasks: `16` (3 of them will be released through PhysioNet)
+- Data format: one JSON object per line (`.jsonl`)
+- Primary use case: benchmark streams for deployment-time learning
+
+DTLBench covers three environment styles used in CASCADE:
+
+- `single-turn`: one input, one final answer
+- `multi-turn`: sequential interaction with the environment
+
+### Summary statistics of the DTLBench. The maximum steps refer to the maximum number of interaction steps that the environment allows per task.
+
+| **Property**                 | **Domain**          | **Task**                                          | **Dataset**       | **Maximum Steps** | **Number of Samples** |
+|------------------------------|---------------------|--------------------------------------------------|-------------------|-------------------|-----------------------|
+| **Single-turn**               | **Medical**         | Medical Diagnosis                                | DDXPlus           | 1                 | 3136                  |
+|                              |                     | Medication Recommendation                        | MIMIC-IV-MR       | 1                 | 2881                  |
+|                              |                     | Medical Specialty Referral                       | MIMIC-IV-MSR      | 1                 | 2115                  |
+|                              |                     | Triage Level Prediction                          | MIMIC-IV-TLP      | 1                 | 2200                  |
+|                              | **Legal**           | Multi-Defendant Legal Charge Prediction          | MUD               | 1                 | 1740                  |
+|                              |                     | Penalty Legal Prediction                         | CMDL              | 1                 | 2080                  |
+|                              | **Financial**       | Financial Customer Intent Routing                | Banking77         | 1                 | 5000                  |
+|                              |                     | Entity-Aware Financial Sentiment Analysis        | SEntFiN           | 1                 | 2299                  |
+|                              | **AIOps**           | AIOps Root Cause Analysis                        | RCA               | 1                 | 2925                  |
+|                              |                     | AIOps Log Fault Diagnosis                        | LFD               | 1                 | 3000                  |
+|                              | **Coding**          | Text-to-SQL                                      | SPIDER            | 1                 | 2147                  |
+|                              |                     | Knowledge-Augmented Text-to-SQL                 | BIRD              | 1                 | 1534                  |
+| **Multi-turn, Simulated**     | **Embodied**        | Household Embodied Decision Making               | ALFWorld          | 30                | 2000                  |
+|                              |                     | Scientific Embodied Decision Making              | ScienceWorld      | 10-30             | 1857                  |
+| **Multi-turn, Real-world**    | **Information Seeking** | Web-based Deep Search                         | 2Wiki             | 5                 | 2500                  |
+|                              | **Medical**         | Complex Tabular Reasoning on Electronic Health Records | MIMIC-III     | 5                 | 2500                  |
+
+## Data Format
+
+Each config can be loaded independently from Hugging Face, and each task keeps the fields needed by its original environment. All tasks include a `task` field, which is the main query or observation presented to the agent.
+
+
+## Load the Dataset
+
+Using `datasets`:
+
+```python
+from datasets import load_dataset
+
+# Load one task
+ddxplus = load_dataset("guosy/DTLBench", "ddxplus")
+print(ddxplus["train"][0])
+
+# Load another task
+spider = load_dataset("guosy/DTLBench", "spider")
+print(spider["train"][0]["task"])
+```
+
+Using `huggingface-cli`:
+
+```bash
+huggingface-cli download --repo-type dataset guosy/DTLBench --local-dir ./DTLBench
+```
+
+## License
+
+DTLBench is a **mixed-license** collection. Each subdataset follows its own original license, and the benchmark authors do not claim additional rights beyond those licenses.
+
+Please see [LICENSE.md](LICENSE.md) and the per-task `LICENSE` files for details. In particular:
+
+- Some tasks are under permissive licenses such as MIT or Apache-2.0
+- Some tasks use CC licenses with attribution or share-alike requirements
+- Some tasks have unclear or unknown redistribution terms
+
+You are responsible for ensuring your use complies with the license of each individual subdataset.
+
+## Citation
+
+If you use DTLBench, please cite the CASCADE paper once it is publicly available. We will update this card with the final bibliography information after release.