Update dataset card: focus on deep-koopman-kan and KANDy benchmarking

README.md

@@ -52,9 +52,9 @@ dataset_info:
 
 # Navier-Stokes Analytical Benchmark
 
-A dataset of 2D incompressible fluid dynamics problems with **closed-form analytical solutions** on a 64x64 grid. Intended as ground-truth supervision for physics-informed neural networks (PINNs), neural operators (FNO, DeepONet), and other scientific ML models.
+A benchmark dataset of 2D incompressible fluid dynamics problems with **closed-form analytical solutions** on a 64x64 grid. Designed for evaluating **deep-koopman-kan** (Koopman-based lifting) and **KANDy** (equation discovery) pipelines on canonical Navier-Stokes flows.
 
-Every sample provides velocity (u, v), pressure (p), and temperature (T) fields computed directly from exact or series-expansion solutions to the Navier-Stokes and energy equations -- no numerical solver is involved.
+Every sample provides velocity (u, v), pressure (p), and temperature (T) fields computed directly from exact or series-expansion solutions -- no numerical solver is involved. The `latex_equation` field serves as the ground-truth reward signal for equation-discovery agents.
 
 ## Dataset Description