On CUAD legal contracts, a prompt-engineered QWEN-2 pipeline with chunking and two answer-selection heuristics reportedly outperforms the fine-tuned DeBERTa-large baseline by about 9%, reaching claimed state-of-the-art performance.
In: Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining (KDD ’96)
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LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents
On CUAD legal contracts, a prompt-engineered QWEN-2 pipeline with chunking and two answer-selection heuristics reportedly outperforms the fine-tuned DeBERTa-large baseline by about 9%, reaching claimed state-of-the-art performance.