Card: describe the difficulty filter stage of the pipeline

README.md

@@ -98,9 +98,9 @@ Source videos come from FineVideo, from LongVILA as released with the OneThinker
 from the long split of Vript. Each video is cut into shots with PySceneDetect and every shot is
 captioned once with MiniMax-M3. A language model then writes two candidate questions per video from
 the captions and a sampled specification, and a judge loop checks each candidate against the captions
-and rewrites it up to three times. The code for all of this is in the repository linked above. The
-released corpus was not difficulty-filtered: `solve_rate = -1.0` and an empty `difficulty_band` in
-`extra_info` mean "not measured".
+and rewrites it up to three times. The pipeline then ends with a difficulty filter that drops
+questions the base model already solves in 6 of 8 rollouts. The code for all of this is in the
+repository linked above.
 
 Because the questions are written from captions rather than from the frames, a caption error can
 reach a label. We report this limitation in the paper.