Research team proposes PALM time-point adaptation method for financial large models
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A research team led by Seunghan Lee et al. released a paper proposing PALM, a time-point adaptation method for financial language models, as an alternative to annual pre-training for financial language models. This method fits low-rank adapters on financial text that the model checkpoint is allowed to read, without modifying any pre-trained weights; the research team validated PALM on ten years of financial news and three types of time-point models with a cutoff time span of twenty years.
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- arXiv q-finPALM: Point-in-time Adaptation for Financial Language Models
This paper proposes PALM (Point-in-time Adaptation for financial Language Models) as an alternative to annual pre-training of financial language models. It achieves adaptation by fitting low-rank adapters on permitted financial text without modifying any pre-trained weights.
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