Papers by Zhenan He
Rationales for Answers to Simple Math Word Problems Confuse Large Language Models (2024.findings-acl)
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| Challenge: | Recent studies show that large language models have advanced mathematical problem-solving abilities in grade school math word problems. |
| Approach: | They propose to combine fine-tuning and prompt-based methods to improve performance . they propose to use a hybrid algorithm to fine- tune LLMs on specific tasks . |
| Outcome: | The proposed methods improve performance on the proposed reasoning process evaluation benchmarks. |
Large Language Models Can Not Perform Well in Understanding and Manipulating Natural Language at Both Character and Word Levels? (2024.findings-emnlp)
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| Challenge: | Large language models (LLMs) still exhibit significant deficiencies in basic language understanding and manipulation. |
| Approach: | They propose a bilingual benchmark to assess the performance of Large language models . they use a set of 15 simple text editing tasks to examine their capabilities . |
| Outcome: | The proposed benchmark aims to assess the performance of Large language models in basic language tasks. |