Papers by Aaditya Bodke

2 papers
PASTEL : Polarity-Aware Sentiment Triplet Extraction with LLM-as-a-Judge (2025.findings-acl)

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Challenge: Existing methods for extracting triplets of aspect terms and opinions are inadequate due to complexity of aspect-opinion interactions and implicit nature of sentiment dependencies in natural language.
Approach: They propose a pipeline that decomposes the ASTE task into structured subtasks . they employ fine-tuned LLMs to separately extract the aspect and opinion terms .
Outcome: The proposed pipeline outperforms existing baselines in the ASTE subtask.
ERU-KG: Efficient Reference-aligned Unsupervised Keyphrase Generation (2025.acl-long)

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Challenge: Existing methods for keyphrase prediction rely on heuristicically defined importance scores . existing methods lack consideration for time efficiency .
Approach: They propose an unsupervised keyphrase generation model that combines informativeness and phraseness modules.
Outcome: The proposed model outperforms baseline models and achieves 89% of the performance of a supervised model for top 10 predictions.

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