Papers by Manav Kapadnis
CLMSM: A Multi-Task Learning Framework for Pre-training on Procedural Text (2023.findings-emnlp)
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| Challenge: | Existing methods to solve procedural reasoning tasks are limited by the prior art. |
| Approach: | They propose a domain-specific, continual pre-training framework that learns from a large set of procedural recipes. |
| Outcome: | The proposed framework outperforms baselines on recipes (in-domain) but is able to generalize to open-domain procedural NLP tasks. |
Evaluating the Effectiveness of Large Language Models in Establishing Conversational Grounding (2024.emnlp-main)
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| Challenge: | despite its importance, there has been limited research on conversational grounding in recent years . pre-trained language models have been costly and time-consuming to evaluate . |
| Approach: | They evaluate the performance of large language models in various aspects of conversational grounding . they propose ways to enhance the capabilities of the models that lag in this aspect . |
| Outcome: | The proposed model performance is based on pre-trained language models and a large pre-training dataset. |
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. |