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README.md

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+---
+license: apache-2.0
+pretty_name: TIPS Training Data
+configs:
+- config_name: math
+  data_files:
+  - split: train
+    path: math/train.parquet
+- config_name: agent
+  data_files:
+  - split: train
+    path: agent/train.parquet
+---
+
+# TIPS Training Data
+
+Outcome-labeled training trajectories used by **TIPS (Thinking-Induced Process Supervision)**.
+
+| Configuration | File | Examples |
+| --- | --- | ---: |
+| Math | `math/train.parquet` | 3,200 |
+| Agent | `agent/train.parquet` | 2,905 |
+
+TIPS trains a generative reward model to produce a reasoning chain, step-level labels, and an outcome label while using only outcome correctness as the reinforcement-learning reward.
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+math_data = load_dataset("XingYing-stack/TIPS-Training-Data", "math", split="train")
+agent_data = load_dataset("XingYing-stack/TIPS-Training-Data", "agent", split="train")
+```
+
+Data preparation and training code are available at https://github.com/RUCBM/TIPS.
+
+## Sources and Licenses
+
+The math data is derived from SCAN-Pro, released under Apache-2.0. The agent data is derived from AgentProcessBench resources, released under MIT. Please also follow the terms of the original data sources.
+

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