Update README.md

README.md

@@ -16,11 +16,10 @@ configs:
     path: data/test-*.parquet
 ---
 
-# SciDocBench: Anonymous Review Data
+# SciDocBench
 
-This review snapshot contains the benchmark data accompanying the submission.
-It retains the original questions, references, images, and four matched views;
-only identifying release-card information has been removed.
+Scientific document understanding benchmark with expert-authored questions,
+reference answers, source images, and four matched evaluation settings.
 
 ## Contents
 
@@ -28,31 +27,32 @@ There are 124 underlying questions and 496 evaluation instances across English
 and Chinese, each paired with all-images-first and interleaved document inputs.
 The release includes 2,758 distinct images and 7,052 image references.
 
-- SciDocBench.tsv: portable VLMEvalKit-compatible benchmark.
-- scidocbench.tsv: compatibility alias of the same table.
-- data/test-00000-of-00001.parquet: the Hugging Face test split.
-- images/SciDocBench/: content-addressed images.
-- manifests/images.jsonl: image hashes and reference counts.
-- release_manifest.json: data counts and checksums.
+- `SciDocBench.tsv`: portable VLMEvalKit-compatible benchmark.
+- `data/test-00000-of-00001.parquet`: the same questions as a Hugging Face test split.
+- `images/SciDocBench/`: content-addressed images.
+- `manifests/images.jsonl`: image hashes and reference counts.
+- `release_manifest.json`: data counts and checksums.
+
+The TSV and Parquet files are two representations of the same benchmark, not
+different question sets.
 
 ## Offline Usage
 
 Download the files through the anonymous repository interface. Place
-SciDocBench.tsv under your VLMEvalKit LMUData directory and copy
-images/SciDocBench/ into LMUData/images/SciDocBench/.
-The TSV image_path entries are relative to the VLMEvalKit image root;
-Parquet images entries are relative to this repository. Keep interleaved
+`SciDocBench.tsv` under your VLMEvalKit `LMUData` directory and copy
+`images/SciDocBench/` into `LMUData/images/SciDocBench/`.
+The TSV `image_path` entries are relative to the VLMEvalKit image root;
+Parquet `images` entries are relative to this repository. Keep interleaved
 segments in their recorded order.
 
 For local tabular analysis:
 
 ```python
 from datasets import load_dataset
-benchmark = load_dataset("parquet", data_files="data/test-00000-of-00001.parquet", split="train")
+benchmark = load_dataset("parquet", data_files={"test": "data/test-00000-of-00001.parquet"}, split="test")
 ```
 
-The local loader's split label does not change the benchmark's evaluation-only
-role. Do not use these test questions for training.
+Do not use these evaluation questions for training.
 
 ## Evaluation