Add paper and code links

README.md

@@ -1,27 +1,29 @@
 ---
+language:
+- en
 license: other
+size_categories:
+- 1K<n<10K
 task_categories:
-  - video-text-to-text
-  - visual-question-answering
-language:
-  - en
+- video-text-to-text
+- visual-question-answering
 tags:
-  - video-understanding
-  - reinforcement-learning
-  - adaptive-reasoning
-size_categories:
-  - 1K<n<10K
+- video-understanding
+- reinforcement-learning
+- adaptive-reasoning
 configs:
-  - config_name: default
-    data_files:
-      - split: train
-        path: train.parquet
+- config_name: default
+  data_files:
+  - split: train
+    path: train.parquet
 ---
 
 # EVAThink-Dataset-Stage1
 
-<!-- TODO(author): paper title / arXiv link, code repo link -->
-<!-- TODO(author): confirm the license field. The frames come from third-party video datasets (see "Source data"). -->
+## Paper & Code
+
+- Paper: [EVAThink: Evidence Sufficiency-Guided Training for Adaptive Thinking in Video Understanding](https://arxiv.org/abs/2611.13907)
+- Code: [GitHub repository](https://github.com/ChangtiWu/EVAThink)
 
 Training data for **stage 1** of the two-stage reinforcement learning that produces
 [EVAThink-Qwen3](https://huggingface.co/MaplesWCT/EVAThink-Qwen3), a video-language model that decides per question
@@ -97,7 +99,8 @@ import pyarrow.parquet as pq
 
 rows = pq.read_table("train.parquet").to_pylist()
 r = rows[0]
-r["prompt"][0]["content"]         # "<video>\n" + question + options + instruction
+r["prompt"][0]["content"]         # "<video>
+" + question + options + instruction
 r["videos"][0]["video"]           # 32 frame paths, relative to the dataset folder
 r["reward_model"]["ground_truth"] # option letter
 r["extra_info"]["view"]           # "dense" or "sparse"
@@ -151,4 +154,4 @@ Both stages train on the two views of a problem in the same update.
 
 The frames are extracted from videos of the datasets named in `data_source`. `samples.jsonl` gives the source video of
 every row as a path inside our local copy. The source videos themselves are not redistributed here, and each source
-dataset remains under its own license and terms.
+dataset remains under its own license and terms.