Papers by Mohammadreza Pourreza
DTS-SQL: Decomposed Text-to-SQL with Small Large Language Models (2024.findings-emnlp)
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| Challenge: | relying on proprietary Large Language Models poses privacy and cost implications for models. |
| Approach: | They propose a two-stage fine-tuning approach that breaks down the task into two simpler tasks. |
| Outcome: | The proposed method achieves 60.31% execution accuracy on Bird hold-out test set . it is the highest performance among methods using 7B parameter models . |
Evaluating Cross-Domain Text-to-SQL Models and Benchmarks (2023.emnlp-main)
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| Challenge: | Text-to-SQL benchmarks are used to evaluate progress made in the field . however, matching a model-generated SQL query to a reference SQL query fails due to various reasons. |
| Approach: | They conduct an extensive evaluation of text-to-SQL benchmarks and re-evaluate some of the top-performing models. |
| Outcome: | The results show that a recent model surpasses the gold standard reference queries in the Spider benchmark in human evaluation. |
DeTriever: Decoder-representation-based Retriever for Improving NL2SQL In-Context Learning (2025.coling-main)
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Raymond Li, Yuxi Feng, Zhenan Fan, Giuseppe Carenini, Weiwei Zhang, Mohammadreza Pourreza, Yong Zhang
| Challenge: | In-context Learning (ICL) has proven to be effective in a variety of complex tasks, but the selection of the most beneficial demonstration examples remains an open research problem. |
| Approach: | They propose a demonstration retrieval framework that learns a weighted combination of LLM hidden states where rich semantic information is encoded. |
| Outcome: | Experiments on two popular NL2SQL benchmarks show that the proposed method outperforms state-of-the-art models. |