Papers by Youbo Lei
Prompt Space Optimizing Few-shot Reasoning Success with Large Language Models (2024.findings-naacl)
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| Challenge: | Prompt engineering is an essential technique for enhancing the abilities of large language models (LLMs) by providing explicit and specific instructions. |
| Approach: | They propose a new approach that uses text embeddings to obtain basis vectors by matrix decomposition and constructs a space for representing all prompts. |
| Outcome: | The proposed approach significantly outperforms state-of-the-art prompt paradigms on ten public reasoning benchmarks. |
MCAD: Multi-teacher Cross-modal Alignment Distillation for efficient image-text retrieval (2024.findings-naacl)
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| Challenge: | Large-scale visual-language pretraining models have shown remarkable capabilities in understanding both vision and language. |
| Approach: | They propose a multi-teacher cross-modality alignment distillation technique to integrate the advantages of single-stream and dual-stream models. |
| Outcome: | The proposed model is lightweight and has only 100M running memory and 8.0ms search latency. |