WDE: Elegantly Forecasting Power Load through Advanced Signal Refinement and Graceful Normalization Approach

The purpose of this paper is to explore the application of large language models (LLMs) in legalcase retrieval and to evaluate their potential for providing legal professionals with more efffcientwork aids. Currently, although pre-trained models have made great progress in legal case retrieval, they are often limited to speciffc types of laws (e.g., criminal law, civil law, etc.) and lackthe ability to generalize across different types of laws. Moreover, most models can only dealwith a single task, whereas the legal case retrieval task requires a model to have a superb comprehension of legal texts, involving multiple subtasks and requiring multitasking capabilities.Therefore, the large language model, which has super generalization ability and multitaskingability, can solve the above problems.In order to explore the application of large language models for legal case retrieval in the legal domain, this paper evaluates a series of emerging largelanguage models, including multilingual models, homegrown large models, and models speciffcally designed for the legal domain. These models are employed to address legal case retrievaland its associated subtasks. Based on the Supreme People’s Court’s deffnition, the legal caseretrieval task is broken down into seven subtasks: event detection, fact generation, trigger wordextraction, keywords extraction, summarization, dispute focus identiffcation, and reasoning generation. Using a range of evaluation metrics, the experiments demonstrated that these emergingmodels have signiffcant potential in the ffeld of legal case retrieval, even with few-shot samples.The research in this paper not only introduces new ideas in the ffeld of legal case retrievalbut also empirically veriffes the potential of LLMs to improve the quality and efffciency of retrieval. It proves the value of large language models in this ffeld and is expected to signiffcantlyenhance the efffciency of legal practitioners, as well as promote the consistency and fairness oflegal judgments through the use of emerging technologies.