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오늘의 자연어 처리572

[2023-12-12] 오늘의 자연어처리 Improving Neural Machine Translation by Multi-Knowledge Integration with Prompting Abstract:Improving neural machine translation (NMT) systems with prompting has achieved significant progress in recent years. In this work, we focus on how to integrate multi-knowledge, multiple types of knowledge, into NMT models to enhance the performance with prompting. We propose a unified framework, which can.. 2023. 12. 12.
[2023-12-11] 오늘의 자연어처리 A Study on the Calibration of In-context Learning Abstract:Modern auto-regressive language models are trained to minimize log loss on broad data by predicting the next token so they are expected to get calibrated answers when framing a problem as a next-token prediction task. We study this for in-context learning (ICL), a widely used way to adapt frozen large language models (LLMs) via crafting .. 2023. 12. 11.
[2023-12-10] 오늘의 자연어처리 PCoQA: Persian Conversational Question Answering Dataset Abstract:Humans seek information regarding a specific topic through performing a conversation containing a series of questions and answers. In the pursuit of conversational question answering research, we introduce the PCoQA, the first \textbf{P}ersian \textbf{Co}nversational \textbf{Q}uestion \textbf{A}nswering dataset, a resource compris.. 2023. 12. 10.
[2023-12-09] 오늘의 자연어처리 nerblackbox: A High-level Library for Named Entity Recognition in Python Abstract:We present nerblackbox, a python library to facilitate the use of state-of-the-art transformer-based models for named entity recognition. It provides simple-to-use yet powerful methods to access data and models from a wide range of sources, for fully automated model training and evaluation as well as versatile mode.. 2023. 12. 9.
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