Tighten intro; clarify eukaryote_cls is within-eukaryote

README.md

@@ -303,13 +303,12 @@ configs:
 
 # GenomeQA
 
-GenomeQA is a diagnostic question-answering benchmark for evaluating whether general-purpose language models can
-reason directly over raw nucleotide sequences. It presents English questions containing one or more DNA sequences and
-asks the model to select an answer using biological signals such as sequence composition, motifs, and motif context.
-It does not assume a specialized DNA encoder or task-specific model training.
+GenomeQA tests whether a general-purpose language model can answer questions about raw nucleotide sequences, with no
+specialised DNA encoder and no task-specific training. Each question is English text containing one or more DNA
+sequences, answerable from signals such as sequence composition, motifs, and motif context.
 
-The original benchmark contains 5,200 examples—2,600 binary-choice questions and 2,600 four-option multiple-choice
-questions—with sequence lengths from 6 to 1,000 base pairs. It covers six task families:
+5,200 examples — 2,600 binary-choice and 2,600 four-option — with sequences from 6 to 1,000 bp, across six task
+families:
 
 1. enhancer and promoter identification;
 2. splice-site identification;
@@ -323,8 +322,7 @@ questions—with sequence lengths from 6 to 1,000 base pairs. It covers six task
 This repository repackages the benchmark introduced in
 [GenomeQA: Benchmarking General Large Language Models for Genome Sequence Understanding](https://huggingface.co/papers/2604.05774)
 ([arXiv:2604.05774](https://arxiv.org/abs/2604.05774)) by Weicai Long, Yusen Hou, Junning Feng, Houcheng Su, Shuo
-Yang, Donglin Xie, and Yanlin Zhang. **All credit for the benchmark belongs to those authors.** We repackage it in
-Parquet, add the subsets listed below, and use it to evaluate Carbon-X.
+Yang, Donglin Xie, and Yanlin Zhang, as Parquet with the extra subsets listed below. We use it to evaluate Carbon-X.
 
 The paper constructs GenomeQA from established genomic resources: