Answer is All You Need: Instruction-following Text Embedding via Answering the Question (2024.acl-long)
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| Challenge: | Existing methods for encoding instruction information fail to be sensitive to clearer criteria like “evaluate similarity based on emotion” . instead, we propose a different approach, which treats the instruction as a “question” about the input text and encodes the expected answers to obtain the representation accordingly. |
| Approach: | They propose a text embedder that captures characteristics of texts specified by user instructions clarifying the similarity criterion. |
| Outcome: | The proposed model improves instruction-following capabilities when applied to large language models and encoder-based LMs. |
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