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Found 6 papers, 2 papers with code
Constructions Are So Difficult That Even Large Language Models Get Them Right for the Wrong Reasons
In this paper, we make a contribution that can be understood from two perspectives: from an NLP perspective, we introduce a small challenge dataset for NLI with large lexical overlap, which minimises the possibility of models discerning entailment solely based on token distinctions, and show that GPT-4 and Llama 2 fail it with strong bias.
Wav2Gloss: Generating Interlinear Glossed Text from Speech
Thousands of the world's languages are in danger of extinction--a tremendous threat to cultural identities and human language diversity.
GlossLM: Multilingual Pretraining for Low-Resource Interlinear Glossing
A key aspect of language documentation is the creation of annotated text in a format such as interlinear glossed text (IGT), which captures fine-grained morphosyntactic analyses in a morpheme-by-morpheme format.
Hire a Linguist!: Learning Endangered Languages with In-Context Linguistic Descriptions
On the contrary, we observe that 2000 endangered languages, though without a large corpus, have a grammar book or a dictionary.
Construction Grammar Provides Unique Insight into Neural Language Models
Construction Grammar (CxG) has recently been used as the basis for probing studies that have investigated the performance of large pretrained language models (PLMs) with respect to the structure and meaning of constructions.
Language Embeddings for Typology and Cross-lingual Transfer Learning
Cross-lingual language tasks typically require a substantial amount of annotated data or parallel translation data.
Cross-Lingual Natural Language Inference
Cross-Lingual Transfer
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