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cs.CL2024
Best Practices and Lessons Learned on Synthetic Data
Ruibo Liu, Jerry Wei, Fangyu Liu +8
The success of AI models relies on the availability of large, diverse, and high-quality datasets, which can be challenging to obtain due to data scarcity, privacy concerns, and hig…
cs.CL2024
Naive Bayes-based Context Extension for Large Language Models
Jianlin Su, Murtadha Ahmed, Wenbo +3
Large Language Models (LLMs) have shown promising in-context learning abilities. However, conventional In-Context Learning (ICL) approaches are often impeded by length limitations…
cs.CL2023
Training Socially Aligned Language Models on Simulated Social Interactions
Ruibo Liu, Ruixin Yang, Chenyan Jia +5
Social alignment in AI systems aims to ensure that these models behave according to established societal values. However, unlike humans, who derive consensus on value judgments thr…