update README

README.md

@@ -108,7 +108,7 @@ These comprehensive evaluations test real-world end-to-end coding and agentic to
 >- Terminal-Bench: All scores are evaluated with the official claude-code from the original [Terminal-Bench](https://www.tbench.ai/) repository(commit `94bf692`), averaged over 8 runs to report the mean pass rate.
 >- ArtifactsBench: All Scores are computed by averaging three runs with the official implementation of [ArtifactsBench](https://github.com/Tencent-Hunyuan/ArtifactsBenchmark), using the stable Gemini-2.5-Pro as the judge model.
 >- BrowseComp & BrowseComp-zh & GAIA (text only) & xbench-DeepSearch: All scores reported use the same agent framework as [WebExplorer](https://arxiv.org/pdf/2509.06501) (Liu et al. 2025), with minor tools description adjustment. We use the 103-sample text-only GAIA validation subset following [WebExplorer](https://arxiv.org/pdf/2509.06501) (Liu et al. 2025).
->- HLE (w/ tools): All reported scores are obtained using search tools and a Python tool. The search tools employ the same agent framework as [WebExplorer](https://arxiv.org/pdf/2509.06501) (Liu et al. 2025), and the Python tool runs in a Jupyter environment.
+>- HLE (w/ tools): All reported scores are obtained using search tools and a Python tool. The search tools employ the same agent framework as [WebExplorer](https://arxiv.org/pdf/2509.06501) (Liu et al. 2025), and the Python tool runs in a Jupyter environment. We use the text-only HLE subset.
 >- τ²-Bench: All scores reported use "extended thinking with tool use", and employ GPT-4.1 as the user simulator.
 >- FinSearchComp-global: Official results are reported for GPT-5-Thinking, Gemini 2.5 Pro, and Kimi-K2. Other models are evaluated using the open-source [FinSearchComp](https://arxiv.org/pdf/2509.13160) (Hu et al. 2025) framework using both  search and Python tools, launched simultaneously for consistency.
 >- AgentCompany: All scores reported use OpenHands 0.42 agent framework.