Papers by Zian Xu
Is ChatGPT a Financial Expert? Evaluating Language Models on Financial Natural Language Processing (2023.findings-emnlp)
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| Challenge: | Large language models (LLMs) have revolutionized general natural language preprocessing tasks, but their performance in financial domains is not evaluated comprehensively. |
| Approach: | They propose a framework to evaluate financial language models on financial tasks . they compare performance of auto-encoding language models and ChatGPT . |
| Outcome: | The proposed framework compares the performance of auto-encoding language models and the LLM ChatGPT on financial tasks. |
Sanitizing Large Language Models in Bug Detection with Data-Flow (2024.findings-emnlp)
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| Challenge: | Large language models (LLMs) have potential in code reasoning tasks but the hallucination effect can compromise the reliability of bug reports. |
| Approach: | They propose a new schema of bug detection that enforces LLMs to emit data-flow paths in few-shot chain-of-thought prompting and validates them via the program-property decomposition. |
| Outcome: | The proposed approach achieves 91.03% precision and 74.00% recall upon synthetic benchmarks and boosts precision by 21.99% with the sanitization. |
Walking in Others’ Shoes: How Perspective-Taking Guides Large Language Models in Reducing Toxicity and Bias (2024.emnlp-main)
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| Challenge: | Existing prompting methods that require white-box access to the model or substantial training fail to simultaneously lessen toxicity and bias. |
| Approach: | They propose a strategy that encourages LLMs to integrate diverse human perspectives and self-regulate their responses by incorporating diverse human viewpoints. |
| Outcome: | The proposed approach can significantly diminish toxicity (up to 89%) and bias (up 73%) in LLMs’ responses. |