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Found 8 papers, 6 papers with code
Learning and Evaluating Chinese Idiom Embeddings
We find that our method substantially outperforms existing methods on the evaluation dataset we have constructed.
Does BERT Understand Idioms? A Probing-Based Empirical Study of BERT Encodings of Idioms
Understanding idioms is important in NLP.
MoZIP: A Multilingual Benchmark to Evaluate Large Language Models in Intellectual Property
In this paper, we contribute a new benchmark, the first Multilingual-oriented quiZ on Intellectual Property (MoZIP), for the evaluation of LLMs in the IP domain.
HiJoNLP at SemEval-2022 Task 2: Detecting Idiomaticity of Multiword Expressions using Multilingual Pretrained Language Models
This paper describes an approach to detect idiomaticity only from the contextualized representation of a MWE over multilingual pretrained language models.
One Model, Multiple Modalities: A Sparsely Activated Approach for Text, Sound, Image, Video and Code
Moreover, our model supports self-supervised pretraining with the same sparsely activated way, resulting in better initialized parameters for different modalities.
Exploring and Adapting Chinese GPT to Pinyin Input Method
We find that a frozen GPT achieves state-of-the-art performance on perfect pinyin.
Investigating Math Word Problems using Pretrained Multilingual Language Models
In this paper, we revisit math word problems~(MWPs) from the cross-lingual and multilingual perspective.
A BERT-based Dual Embedding Model for Chinese Idiom Prediction
Specifically, we first match the embedding of each candidate idiom with the hidden representation corresponding to the blank in the context.
