Papers by Eun-Sol Kim

3 papers
Semantic Alignment with Calibrated Similarity for Multilingual Sentence Embedding (2021.findings-emnlp)

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Challenge: Existing methods for learning semantic similarity between two English sentences have focused on one sub-task and therefore showed biased performance.
Approach: They propose a method to learn semantic similarity between two English sentences using siamese networks.
Outcome: The proposed method improves on both sub-tasks and predicts similarity scores in 14 languages.
Hypergraph Transformer: Weakly-Supervised Multi-hop Reasoning for Knowledge-based Visual Question Answering (2022.acl-long)

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Challenge: Existing knowledge-based visual question answering tasks require weak supervision and no visual knowledge.
Approach: They propose a model which encodes high-level semantics of a question and a knowledge base and learns high order associations between them.
Outcome: The proposed model encodes high-level semantics of a question and a knowledge base, and learns high order associations between them.
Selective Token Generation for Few-shot Natural Language Generation (2022.coling-1)

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Challenge: Experimental results show that the proposed selective token generation algorithm outperforms the previous additive learning algorithms based on the PLMs.
Approach: They propose an additive learning algorithm that selectively outputs language tokens between a task-general PLM and a specific adapter during training and inference.
Outcome: The proposed algorithm outperforms existing methods on few-shot natural language generation tasks.

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