Papers with BNs

2 papers
Linguistically-Motivated Yorùbá-English Machine Translation (2022.coling-1)

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Challenge: Several phenomena where asymmetry arises have been identified as challenging problems for machine translation.
Approach: They perform a fine-grained analysis of how an SMT system compares with two NMT systems when translating bare nouns into English.
Outcome: The proposed model outperforms the SMT and BiLSTM models for 4 categories and the BiLST outperformed the SLT models for 3 categories.
Scalability of Bayesian Network Structure Elicitation with Large Language Models: a Novel Methodology and Comparative Analysis (2025.coling-main)

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Challenge: Existing methods for BN structure learning are limited by the size of the BN.
Approach: They propose a method for Bayesian Networks (BNs) structure elicitation that initializes several LLMs with different experiences and queries them to create a structure.
Outcome: The proposed method performs better than the existing method with one of the three studied LLMs, but the performance decreases with the increase in BN size.

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