Papers by Konstantinos Papakostas

2 papers
Probing LLMs for Joint Encoding of Linguistic Categories (2023.findings-emnlp)

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Challenge: Existing research suggests that a linguistic hierarchy emerges in large language models . little is known about how encodings of different linguistic phenomena interact within the models - and to what extent processing of linguistically-related categories relies on the same, shared model representations.
Approach: They propose a framework for testing the joint encoding of linguistic categories in large language models.
Outcome: The proposed framework shows that the same patterns hold across languages in multilingual LLMs.
Model Analysis & Evaluation for Ambiguous Question Answering (2023.findings-acl)

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Challenge: Ambiguous questions are a challenge for Question Answering models as they require answers that cover multiple interpretations of the original query.
Approach: They aim to investigate whether model/data scaling improves the answers’ quality and whether automated metrics align with human judgment.
Outcome: The proposed models can generate long-form answers that combine conflicting information and provide valuable insights into the limitations of the current approaches.

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