debias
DeepSeek-R1-Distill-Llama-8B-Debiased-i1-GGUFdebiased-granite-3.2-8b-instruct-i1-GGUFQwen-SEA-LION-v4-4B-VL-debiased-i1-GGUFDeepSeek-R1-Distill-Llama-8B-Debiased-GGUFQwen-SEA-LION-v4-4B-VL-debiased-GGUFdebiased-granite-3.2-8b-instruct-GGUFdistilroberta-base-finetuned-winogrande_debiaseddistilbert-base-cased-gradiend-gender-debiased
Datasets
All datasets matching “debias”vsi-bench-debiased-evalgen_debiased_nli
Overview
Original dataset available here.
@inproceedings{gen-debiased-nli-2022,
title = "Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets",
author = "Wu, Yuxiang and
Gardner, Matt and
Stenetorp, Pontus and
Dasigi, Pradeep",
booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics",
month = may,
year = "2022",
publisher = "Association for Computational… See the full description on the dataset page: https://huggingface.co/datasets/pietrolesci/gen_debiased_nli.epidemic_sound_effects_t5_debiasedlaion_text_debiased_60MFilter zxbsmk/laion_text_debiased_60M by image size and get 512 subset(12,009,641 pairs), 768 subset(4,915,850 pairs), 1024 subset(1,985,026 pairs).
verifier-debias-v2
verifier-debias-v2 — de-biased SFT data for a generative verifier
This dataset was presented in the paper One Token to Fool LLM-as-a-Judge.
GitHub repository: yulaizhao/Master-RM
SFT data to train a generative verifier (GenRM, arXiv:2408.15240)
from Qwen/Qwen2.5-7B-Instruct. Each row is a conversational example
(messages = system + user + gold assistant) plus a verdict (PASS/FAIL) and
the underlying 1–5 score. The assistant target is a critique ending in
Verdict: PASS / Verdict:… See the full description on the dataset page: https://huggingface.co/datasets/narcolepticchicken/verifier-debias-v2.laion_text_debiased_100M
100M Text Debiased Subset from LAION 2B
Captions in LAION-2B have a significant bias towards describing visual text content embedded in the images.
Released CLIP models have strong text spotting bias in almost every style of web images, resulting in the CLIP-filtering datasets inherently biased towards visual text dominant data.
CLIP models easily learn text spotting capacity from parrot captions while failing to connect the vision-language semantics, just like a text spotting… See the full description on the dataset page: https://huggingface.co/datasets/linyq/laion_text_debiased_100M.