Papers by Chongjun Wang
Trustworthiness and Self-awareness in Large Language Models: An Exploration through the Think-Solve-Verify Framework (2024.lrec-main)
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| Challenge: | Large Language Models (LLMs) are becoming increasingly influential in reasoning tasks, but they lack trustworthiness and introspective self-awareness when subjected to complex reasoning tasks. |
| Approach: | They propose a framework to explore LLMs’ trustworthiness, introspective self-awareness, and collaborative reasoning by using the Think-Solve-Verify framework. |
| Outcome: | The proposed approach improves from 67.3% to 72.8% on the AQuA dataset and demonstrates the model’s ability to explain the given answers. |