Papers by Hamed Rahimi
Contextualized Topic Coherence Metrics (2024.findings-eacl)
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| Challenge: | Existing topic models that estimate the interpretability of topics are difficult to compare due to their nature as unsupervised models. |
| Approach: | They propose to use contextualized topic coherence metrics to simulate human-centered coherency evaluation while maintaining the efficiency of other automated methods. |
| Outcome: | The proposed metrics better reflect human judgment on topics extracted from short text collections by avoiding highly scored topics that are meaningless to humans. |
You can’t pick your neighbors, or can you? When and How to Rely on Retrieval in the kNN-LM (2022.findings-emnlp)
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| Challenge: | Recent studies have shown that retrieval-enhanced language models can improve perplexity by combining text from large external datastores with a k-nearest neighbors model. |
| Approach: | They propose a retrieval-enhanced language model that interpolates existing LMs with a k-nearest neighbors model and requires no additional training. |
| Outcome: | The proposed model improves on two English language modeling datasets and shows that it is most effective when items have high semantic similarity with the query. |