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Found 4 papers, 3 papers with code
From One to Many: Expanding the Scope of Toxicity Mitigation in Language Models
To date, toxicity mitigation in language models has almost entirely been focused on single-language settings.
Goodtriever: Adaptive Toxicity Mitigation with Retrieval-augmented Models
Considerable effort has been dedicated to mitigating toxicity, but existing methods often require drastic modifications to model parameters or the use of computationally intensive auxiliary models.
When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale
In this work, we take a wider view and explore scalable estimates of data quality that can be used to systematically measure the quality of pretraining data.
On the Challenges of Using Black-Box APIs for Toxicity Evaluation in Research
We evaluate the implications of these changes on the reproducibility of findings that compare the relative merits of models and methods that aim to curb toxicity.
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