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The task_categories "preference-modeling" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
LitBench Preference Pairs (chat format)
This dataset consolidates the LitBench train and test preference pairs into one repository with two splits: train and test. Each example contains two chat-style conversations under keys chosen and rejected, plus numeric scores score_chosen and score_rejected.
Last updated: 2025-10-04 05:15 UTC
Splits
- train: 43827 examples
- test: 0 examples
Features
chosen: list of role/content messages representing the preferred conversationrejected: list of role/content messages representing the alternative conversationscore_chosen: integer upvote score of the chosen storyscore_rejected: integer upvote score of the rejected story
Loading
from datasets import load_dataset
ds = load_dataset("CarlOwOs/LitBench-Processed")
print(ds)
Citation
If you use this dataset, please also acknowledge the original LitBench sources.
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