Abstract
Pre-trained language models (PLMs) leverage chains-of-thought (CoT) to simulate human reasoning and inference processes, achieving proficient performance in multi-hop QA. However, a gap persists between PLMs' reasoning abilities and those of humans when tackling complex problems. Psychological studies suggest a vital connection between explicit information in passages and human prior knowledge during reading. Nevertheless, current research has given insufficient attention to linking input passages and PLMs' pre-training-based knowledge from the perspective of human cognition studies. In this study, we introduce a Prompting Explicit and Implicit knowledge (PEI) framework, which uses prompts to connect explicit and implicit knowledge, aligning with human reading process for multi-hop QA. We consider the input passages as explicit knowledge, employing them to elicit implicit knowledge through unified prompt reasoning. Furthermore, our model incorporates type-specific reasoning via prompts, a form of implicit knowledge. Experimental results show that PEI performs comparably to the state-of-the-art on HotpotQA. Ablation studies confirm the efficacy of our model in bridging and integrating explicit and implicit knowledge.
Original language | English |
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Title of host publication | 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Main Conference Proceedings |
Editors | Nicoletta CALZOLARI, Min-Yen KAN, Veronique HOSTE, Alessandro LENCI, Sakriani SAKTI, Nianwen XUE |
Publisher | European Language Resources Association (ELRA) |
Pages | 13179-13189 |
Number of pages | 11 |
ISBN (Electronic) | 9782493814104 |
Publication status | Published - May 2024 |
Event | Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024 - Hybrid, Torino, Italy Duration: 20 May 2024 → 25 May 2024 |
Publication series
Name | 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Main Conference Proceedings |
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Conference
Conference | Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024 |
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Country/Territory | Italy |
City | Hybrid, Torino |
Period | 20/05/24 → 25/05/24 |
Bibliographical note
Publisher Copyright:© 2024 ELRA Language Resource Association: CC BY-NC 4.0.
Funding
This work is supported by the Alan Turning Institute/DSO grant: Improving multimodality misinformation detection with affective analysis. Yunfei Long, Guangming Huang and Cunjin Luo acknowledge the financial support of the School of Computer science and Electrical Engineering, University of Essex.
Keywords
- Implicit Knowledge
- Multi-hop QA
- Prompt