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Found 3 papers, 2 papers with code
Fine-tuning Large Language Models for Domain-specific Machine Translation
Second, LLMs with fine-tuning on domain-specific data often require high training costs for domain adaptation, and may weaken the zero-shot MT capabilities of LLMs due to over-specialization.
Alignment-based conformance checking over probabilistic events
However, this data is typically characterised by noise and uncertainty, in contrast to the assumption of a deterministic event log required by conformance checking algorithms.
Learning Representations for Time Series Clustering
When applying seq2seq to time series clustering, obtaining a representation that effectively represents the temporal dynamics of the sequence, multi-scale features, and good clustering properties remains a challenge.
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