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Aligning Large Language Models with Counterfactual DPO
Advancements in large language models (LLMs) have demonstrated remarkable capabilities across a diverse range of applications.
Optimising Human-Machine Collaboration for Efficient High-Precision Information Extraction from Text Documents
We argue for the utility of a human-in-the-loop approach in applications where high precision is required, but purely manual extraction is infeasible.
Causal datasheet: An approximate guide to practically assess Bayesian networks in the real world
Here we propose a causal extension to the datasheet concept proposed by Gebru et al (2018) to include approximate BN performance expectations for any given dataset.
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