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joelniklaus

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lextreme

like 22

Joel,

Thanks again for merging the Ukrainian judgment prediction subset into LEXTREME — glad it fits well.

Two things I wanted to bring up:

1. Paper feedback. I've been running fine-tuning experiments on XLM-R and Legal-XLM-R (base + large) for temporal generalization on Ukrainian court decisions — training across three epochs (pre-war, hybrid war, full-scale invasion, 428K decisions). One interesting finding: general-purpose XLM-R outperforms Legal-XLM-R by 7–9 pp, likely due to tokenizer fertility penalties on Cyrillic. The paper cites LEXTREME and MultiLegalPile extensively. Would you be open to a quick look at the draft before submission? Your perspective on the legal model behavior would be very valuable.

2. More Ukrainian tasks for LEXTREME. Beyond judgment prediction, I have several datasets on HF that could become LEXTREME subsets:

• ua-statute-retrieval — statute section retrieval benchmark (already on arXiv: 2605.17639)
• ua-court-citation-graph — citation prediction between court decisions
• ua-temporal-drift — the temporal splits from the paper above

Happy to format these to LEXTREME specs. This would give the benchmark its first Cyrillic/Ukrainian coverage beyond judgment prediction.

3. If there are any legal NLP workshops or communities where this work would be a good fit, I'd appreciate a pointer — I'm relatively new to the venue side of the field.

Best,
Volodymyr