Linguistic Probing of Language Models

Do language models understand structural & theoretical knowledge of language? Language models are known to be aware of structural linguistic knowledge and can process such liguistic things with specific parts(layers or neurons) of them. I’m collaborating with syntaticians (and/or) semanticists, dealing with some linguistic phenomena which seems not likely to be “understood” by language models.

(Human-like) Reasoning Abilities of LLMs

I’m interested about the intermediate reasoning steps that LLMs produce while solving problems - espeically linguistic or cognitive ones. We can obtain their rationales in the form of natural language, and assess the rationales in various points of view. Maybe stuffs from pedagogy or language acquisition can help too.

Dealing with Low-Resource Language(s)

Yes, you like Manchu. Not only Manchu language, there are so many things to do with non-English languages, especially low-resourced ones, in NLP. Especially I’m interested in tokenizers for languages which are not written in Latin alphabets or which are highly agglutinative (yes, Korean!).

Argument Mining

What do people think about a controversial topic? That’s a kind of argumentative data, related to the topic “Argument Mining.” Particularly I’d like to collect and summarize diverse evidences that people propse when they support or attack a stance about the topic. It will require many steps: analyzing the argumentative structure of given texts, identifying necessary arguments or evidences, summarizing or clustering those evidences, and so on.