Papers by Sohan Patnaik
Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning (2025.acl-long)
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| Challenge: | Prior studies have demonstrated that LLMs generate step-by-step rationales, but limited data is available to improve their performance in commercial settings due to copyright and legal issues. |
| Approach: | They propose a trainable framework that tunes a (small) LLM to generate outputs from a pool of diverse rationales that selectively improves the downstream task. |
| Outcome: | The proposed framework outperforms several trainable and prompting baselines on maths problem solving, natural language inference, and commonsense reasoning. |
An Evaluation Framework for Legal Document Summarization (2022.lrec-1)
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| Challenge: | Existing metrics for summarizing legal documents fail to evaluate intent in the original text. |
| Approach: | They propose an automated intent-based summarization metric which shows a better agreement with human evaluation as compared to other automated metrics like BLEU, ROUGE-L etc. |
| Outcome: | The proposed method shows that human evaluation is more accurate than other metrics. |