Fact-based Court Judgment Prediction
This work addresses early-phase case outcome prediction for legal professionals and the public, but it is incremental as it builds directly on existing research with no performance gains.
The paper tackled fact-based court judgment prediction using Indian legal documents, introducing two problem variations based on facts alone and facts with lower court rulings, but found performance declines compared to prior state-of-the-art results.
This extended abstract extends the research presented in "ILDC for CJPE: Indian Legal Documents Corpus for Court Judgment Prediction and Explanation" \cite{malik-etal-2021-ildc}, focusing on fact-based judgment prediction within the context of Indian legal documents. We introduce two distinct problem variations: one based solely on facts, and another combining facts with rulings from lower courts (RLC). Our research aims to enhance early-phase case outcome prediction, offering significant benefits to legal professionals and the general public. The results, however, indicated a performance decline compared to the original ILDC for CJPE study, even after implementing various weightage schemes in our DELSumm algorithm. Additionally, using only facts for legal judgment prediction with different transformer models yielded results inferior to the state-of-the-art outcomes reported in the "ILDC for CJPE" study.