Search Results for author: Rajdeep Mukherjee

Found 13 papers, 11 papers with code

MILDSum: A Novel Benchmark Dataset for Multilingual Summarization of Indian Legal Case Judgments

1 code implementation28 Oct 2023 Debtanu Datta, Shubham Soni, Rajdeep Mukherjee, Saptarshi Ghosh

Automatic summarization of legal case judgments is a practically important problem that has attracted substantial research efforts in many countries.

ECTSum: A New Benchmark Dataset For Bullet Point Summarization of Long Earnings Call Transcripts

1 code implementation22 Oct 2022 Rajdeep Mukherjee, Abhinav Bohra, Akash Banerjee, Soumya Sharma, Manjunath Hegde, Afreen Shaikh, Shivani Shrivastava, Koustuv Dasgupta, Niloy Ganguly, Saptarshi Ghosh, Pawan Goyal

Despite tremendous progress in automatic summarization, state-of-the-art methods are predominantly trained to excel in summarizing short newswire articles, or documents with strong layout biases such as scientific articles or government reports.

ETMS@IITKGP at SemEval-2022 Task 10: Structured Sentiment Analysis Using A Generative Approach

1 code implementation SemEval (NAACL) 2022 Raghav R, Adarsh Vemali, Rajdeep Mukherjee

Structured Sentiment Analysis (SSA) deals with extracting opinion tuples in a text, where each tuple (h, e, t, p) consists of h, the holder, who expresses a sentiment polarity p towards a target t through a sentiment expression e. While prior works explore graph-based or sequence labeling-based approaches for the task, we in this paper present a novel unified generative method to solve SSA, a SemEval2022 shared task.

Sentence Sentiment Analysis

PASTE: A Tagging-Free Decoding Framework Using Pointer Networks for Aspect Sentiment Triplet Extraction

1 code implementation EMNLP 2021 Rajdeep Mukherjee, Tapas Nayak, Yash Butala, Sourangshu Bhattacharya, Pawan Goyal

Aspect Sentiment Triplet Extraction (ASTE) deals with extracting opinion triplets, consisting of an opinion target or aspect, its associated sentiment, and the corresponding opinion term/span explaining the rationale behind the sentiment.

Aspect Sentiment Triplet Extraction Sentence

Understanding the Role of Affect Dimensions in Detecting Emotions from Tweets: A Multi-task Approach

1 code implementation9 May 2021 Rajdeep Mukherjee, Atharva Naik, Sriyash Poddar, Soham Dasgupta, Niloy Ganguly

For the regression task, VADEC, when trained with SenWave, achieves 7. 6% and 16. 5% gains in Pearson Correlation scores over the current state-of-the-art on the EMOBANK dataset for the Valence (V) and Dominance (D) affect dimensions respectively.

Emotion Classification regression +1

How Have We Reacted To The COVID-19 Pandemic? Analyzing Changing Indian Emotions Through The Lens of Twitter

no code implementations20 Aug 2020 Rajdeep Mukherjee, Sriyash Poddar, Atharva Naik, Soham Dasgupta

Since its outbreak, the ongoing COVID-19 pandemic has caused unprecedented losses to human lives and economies around the world.

Emotion Classification

StationPlot: A New Non-stationarity Quantification Tool for Detection of Epileptic Seizures

no code implementations10 Nov 2018 Sawon Pratiher, Subhankar Chattoraj, Rajdeep Mukherjee

A novel non-stationarity visualization tool known as StationPlot is developed for deciphering the chaotic behavior of a dynamical time series.

EEG Electroencephalogram (EEG) +3

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