Papers by Manuj Malik
Evaluating LLMs’ Mathematical Reasoning in Financial Document Question Answering (2024.findings-acl)
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| Challenge: | Large Language Models excel in natural language understanding, but their capability for complex mathematical reasoning with a hybrid of structured tables and unstructured text remain uncertain. |
| Approach: | They propose a prompting technique tailored to semi-structured documents that matches or outperforms baselines performance while providing a nuanced understanding of LLMs' abilities. |
| Outcome: | The proposed prompting technique outperforms baseline prompting techniques while providing a nuanced understanding of LLMs' abilities. |
An Empirical Analysis of the Writing Styles of Persona-Assigned LLMs (2024.emnlp-main)
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| Challenge: | Recent efforts to "personalize" large language models by assigning them specific personas are limited by current knowledge of how well they perform. |
| Approach: | They use a style embedding model to analyze writing styles of persona-assigned LLMs . they find significant style differences between personas using Kullback-Leibler divergence . |
| Outcome: | The proposed model shows significant differences in writing styles among personas across socio-demographic groups. |