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README.md

@@ -2,12 +2,13 @@
 license: cc-by-nc-4.0
 pretty_name: AnyMo Bench
 task_categories:
-- time-series-classification
+- other
 tags:
 - human-activity-recognition
 - imu
 - wearable-sensing
 - time-series
+- timeseries
 - in-the-wild
 - nymeria
 configs:
@@ -39,9 +40,9 @@ configs:
 
 # AnyMo Bench
 
-AnyMo Bench is a challenging fine-grained in-the-wild HAR benchmark built from real wearable IMU streams in the Nymeria dataset. It provides subject-disjoint and cross-device evaluation settings for wearable motion recognition.
+AnyMo Bench is a challenging fine-grained in-the-wild HAR benchmark built from real wearable IMU streams in the Nymeria dataset. It provides unseen-subject and cross-device evaluation settings for wearable motion recognition.
 
-The benchmark contains 154,695 eligible activity intervals from 196 subjects, covering 211.6 hours of real in-the-wild IMU data. IMU streams are synchronized to a common 60 Hz temporal grid. Each row contains one activity segment with an `imu` array of shape `[T, 18]`, where `T <= 300` and the 18 channels concatenate one selected IMU from each of Head, Left Wrist, and Right Wrist.
+The benchmark contains 154,695 eligible activity windows from 196 subjects, covering 211.6 hours of real in-the-wild IMU data. IMU streams are synchronized to a common 60 Hz temporal grid. Each row contains one activity window with an `imu` array of shape `[T, 18]`, where `T <= 300` and the 18 channels concatenate one selected IMU from each of Head, Left Wrist, and Right Wrist.
 
 ## Configurations
 
@@ -73,7 +74,7 @@ Channel order:
 head_acc_x, head_acc_y, head_acc_z, head_gyro_x, head_gyro_y, head_gyro_z, left_wrist_acc_x, left_wrist_acc_y, left_wrist_acc_z, left_wrist_gyro_x, left_wrist_gyro_y, left_wrist_gyro_z, right_wrist_acc_x, right_wrist_acc_y, right_wrist_acc_z, right_wrist_gyro_x, right_wrist_gyro_y, right_wrist_gyro_z
 ```
 
-The exported IMU values are the processed 60 Hz benchmark windows before model-specific normalization. Shorter-than-5-second windows are not zero-padded in the Parquet files. Intervals longer than 300 timesteps are split into non-overlapping 300-timestep segments, matching the AnyMo Bench evaluation construction.
+The exported IMU values are the processed 60 Hz benchmark windows before model-specific normalization. Shorter-than-5-second windows are not zero-padded in the Parquet files. Windows longer than 300 timesteps are split into non-overlapping 300-timestep segments, matching the AnyMo Bench evaluation construction.
 
 ## Split Summary
 
@@ -86,4 +87,22 @@ The exported IMU values are the processed 60 Hz benchmark windows before model-s
 
 ## License and Source Dataset
 
-AnyMo Bench is curated from Nymeria and follows the Nymeria non-commercial research-use terms. Please cite the Nymeria dataset and the AnyMo Bench release when using this data.
+AnyMo Bench is curated from Nymeria and follows the Nymeria non-commercial research-use terms. Please cite the Nymeria dataset and AnyMo when using this data.
+
+```bibtex
+@article{chen2026anymo,
+  title={AnyMo: Geometry-Aware Setup-Agnostic Modeling of Human Motion in the Wild},
+  author={Chen, Baiyu and Li, Zechen and Wongso, Wilson and Li, Lihuan and Lin, Xiachong and Xue, Hao and Tag, Benjamin and Salim, Flora},
+  journal={arXiv preprint arXiv:2605.22715},
+  year={2026}
+}
+
+@inproceedings{ma2024nymeria,
+  title={Nymeria: A massive collection of multimodal egocentric daily motion in the wild},
+  author={Ma, Lingni and Ye, Yuting and Hong, Fangzhou and Guzov, Vladimir and Jiang, Yifeng and Postyeni, Rowan and Pesqueira, Luis and Gamino, Alexander and Baiyya, Vijay and Kim, Hyo Jin and others},
+  booktitle={European Conference on Computer Vision},
+  pages={445--465},
+  year={2024},
+  organization={Springer}
+}
+```