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pro vyhledávání: '"Jang, Seongbo"'
Auxiliary function is a helpful component to improve language model's code generation ability. However, a systematic exploration of how they affect has yet to be done. In this work, we comprehensively evaluate the ability to utilize auxiliary functio
Externí odkaz:
http://arxiv.org/abs/2403.10575
As language models are often deployed as chatbot assistants, it becomes a virtue for models to engage in conversations in a user's first language. While these models are trained on a wide range of languages, a comprehensive evaluation of their profic
Externí odkaz:
http://arxiv.org/abs/2402.17377
Recently, finetuning a pretrained language model to capture the similarity between sentence embeddings has shown the state-of-the-art performance on the semantic textual similarity (STS) task. However, the absence of an interpretation method for the
Externí odkaz:
http://arxiv.org/abs/2202.13196
Autor:
Park, Sungjoon, Moon, Jihyung, Kim, Sungdong, Cho, Won Ik, Han, Jiyoon, Park, Jangwon, Song, Chisung, Kim, Junseong, Song, Yongsook, Oh, Taehwan, Lee, Joohong, Oh, Juhyun, Lyu, Sungwon, Jeong, Younghoon, Lee, Inkwon, Seo, Sangwoo, Lee, Dongjun, Kim, Hyunwoo, Lee, Myeonghwa, Jang, Seongbo, Do, Seungwon, Kim, Sunkyoung, Lim, Kyungtae, Lee, Jongwon, Park, Kyumin, Shin, Jamin, Kim, Seonghyun, Park, Lucy, Oh, Alice, Ha, Jung-Woo, Cho, Kyunghyun
We introduce Korean Language Understanding Evaluation (KLUE) benchmark. KLUE is a collection of 8 Korean natural language understanding (NLU) tasks, including Topic Classification, SemanticTextual Similarity, Natural Language Inference, Named Entity
Externí odkaz:
http://arxiv.org/abs/2105.09680
Typically, tokenization is the very first step in most text processing works. As a token serves as an atomic unit that embeds the contextual information of text, how to define a token plays a decisive role in the performance of a model.Even though By
Externí odkaz:
http://arxiv.org/abs/2010.02534
Publikováno v:
In Information Sciences May 2020 519:229-242