SlowGuess/NAACL_2022_OCR huggingface dataset:
Table 9: LAS on RU-GSD (Dev) using BAP and DEPPROBE with different LMs (± standard deviation).
MODELS	SOURCE	LAYERS	EMB d	PARAMS	BAP	DEPPROBE
bert-base-multilingual-cased	Devlin et al. (2019)	12	768	178M	87.5±0.1	55.5±0.2
xlm-roberta-base	Conneau et al. (2020)	12	768	278M	90.2±0.1	59.1±0.2
google/rembert	Chung et al. (2021)	32	1152	576M	91.3±0.3	31.7±0.3
KB/bert-base-swedish-cased	Malmsten et al. (2020)	12	768	125M	90.8±0.1	61.7±0.2
Table 10: LAS on SV-Talbanken (Dev) using BAP and DEPPROBE with different LMs (± standard deviation).
MODELS	SOURCE	LAYERS	EMB d	PARAMS	BAP	DEPPROBE
bert-base-multilingual-cased	Devlin et al. (2019)	12	768	178M	84.6±0.4	49.1±0.4
xlm-roberta-base	Conneau et al. (2020)	12	768	278M	85.5±0.3	30.3±0.1
google/rembert	Chung et al. (2021)	32	1152	576M	85.3±0.2	5.2±0.1
bert-base-chinese	Devlin et al. (2019)	12	768	102M	85.8±0.1	46.4±0.1
hfl/chinese-bert-wwm-ext	Cui et al. (2021)	12	768	102M	86.0±0.3	45.8±0.3
hfl/chinese-roberta-wwm-ext	Cui et al. (2021)	12	768	102M	85.9±0.3	47.7±0.4
Table 11: LAS on ZH-GSD (Dev) using BAP and DEPPROBE with different LMs (± standard deviation).