Papers with personalized representations
Compositional Demographic Word Embeddings (2020.emnlp-main)
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| Challenge: | Word embeddings are usually derived from corpora containing text from many individuals . however, they cannot account for user-specific word preferences, such as using the same word in different ways across contexts. |
| Approach: | They propose a new form of personalized word embeddings that use demographic-specific word representations derived compositionally from full or partial demographic information for a user. |
| Outcome: | The proposed representations outperform generic representations on two English language tasks. |
Pre-trained Personalized Review Summarization with Effective Salience Estimation (2023.findings-acl)
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| Challenge: | Pretrained language models (PLMs) are a new paradigm in text generation for the strong ability of natural language comprehension. |
| Approach: | They propose a pre-trained personalized review summarization method that incorporates personalized information into the salience estimation of input reviews. |
| Outcome: | The proposed method performs better than the state-of-the-art methods on real-world datasets. |
ChildEval:WHEN LARGE LANGUAGE MODELS MEET CHILDREN’S PERSONALITIES (2026.findings-acl)
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| Challenge: | Large Language Models (LLMs) have achieved remarkable success in effectively understanding and generating human language, leading to a revolutionary era in LLMs. |
| Approach: | They propose a benchmark to evaluate LLMs' ability to infer and follow child-centered preferences in long-context conversations. |
| Outcome: | The proposed benchmark spans five top-level and fourteen sub-level categories covering children’s daily lives and development. |