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Add dataset card: DiaLLM context, construction, columns, citation, fix license (#1)
Browse files- Add dataset card: DiaLLM context, construction, columns, citation, fix license (63c6b8db05d6d859ccbaab54250a2c190e077a17)
README.md
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---
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license:
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---
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license: mit
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task_categories:
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- text-generation
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language:
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- en
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tags:
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- dialect
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- english-varieties
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- dpo
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- preference-dataset
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size_categories:
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- 10K<n<100K
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---
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# DiaLLM — Pooled Preference Dataset (Implicit Thread)
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Part of **DiaLLM: An Investigation into the Robustness-Generation Gap in
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English Dialect Adaptation** (EMNLP 2026 Main).
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45,690 preference pairs, pooling all three variety-specific sets
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([Australian](https://huggingface.co/datasets/surrey-nlp/alignment-australian-final),
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[Northern British](https://huggingface.co/datasets/surrey-nlp/alignment-british-final),
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[Indian](https://huggingface.co/datasets/surrey-nlp/alignment-indian-final)) without
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variety targeting. Used for **implicit-thread** DPO training, where the three
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varieties are pooled rather than targeted individually, preserving the
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variety-agnostic objective of that thread.
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## Construction
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Built from the UltraFeedback preference dataset ([Cui et al., 2023](https://arxiv.org/abs/2310.01377)),
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via Argilla's cleaned/binarized release ([`argilla/ultrafeedback-binarized-preferences-cleaned`](https://huggingface.co/datasets/argilla/ultrafeedback-binarized-preferences-cleaned), MIT licensed):
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the originally-preferred completion is transformed into a dialectal variant
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using [Multi-VALUE](https://github.com/SALT-NLP/multi-value) ([Ziems et al., 2023](https://arxiv.org/abs/2212.08011)),
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based on eWAVE morphosyntactic features. Code blocks are preserved verbatim
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during conversion.
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## Columns
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| Column | Description |
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|---|---|
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| `prompt` | Original UltraFeedback prompt (standard English, unmodified) |
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| `chosen` | Multi-VALUE dialectal variant of the preferred completion |
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| `rejected` | Original standard-English form of that completion |
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| `prompt_dialect_density` | eWAVE-based dialect feature density of the prompt |
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| `chosen_dialect_density` | eWAVE-based dialect feature density of the chosen completion |
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**Code, checkpoints, linguistic-analysis toolkit:** https://github.com/surrey-nlp/diallm
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**Paper:** https://arxiv.org/abs/2607.07669
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## Citation
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```bibtex
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@article{painter2026diallm,
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title = {DiaLLM: An Investigation into the Robustness-Generation Gap in English Dialect Adaptation},
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author = {Painter, Jordan and Srirag, Dipankar and Kappiyath, Adarsh and Kanojia, Diptesh and Joshi, Aditya and Yin, Lu},
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year = {2026},
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eprint = {2607.07669},
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archivePrefix = {arXiv}
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}
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```
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