Search Results for author: Neha Anna John

Found 6 papers, 2 papers with code

Taxonomy Expansion for Named Entity Recognition

no code implementations22 May 2023 Karthikeyan K, Yogarshi Vyas, Jie Ma, Giovanni Paolini, Neha Anna John, Shuai Wang, Yassine Benajiba, Vittorio Castelli, Dan Roth, Miguel Ballesteros

We experiment with 6 diverse datasets and show that PLM consistently performs better than most other approaches (0. 5 - 2. 5 F1), including in novel settings for taxonomy expansion not considered in prior work.

named-entity-recognition Named Entity Recognition +2

A Weak Supervision Approach for Few-Shot Aspect Based Sentiment

no code implementations19 May 2023 Robert Vacareanu, Siddharth Varia, Kishaloy Halder, Shuai Wang, Giovanni Paolini, Neha Anna John, Miguel Ballesteros, Smaranda Muresan

We explore how weak supervision on abundant unlabeled data can be leveraged to improve few-shot performance in aspect-based sentiment analysis (ABSA) tasks.

Aspect-Based Sentiment Analysis Aspect Extraction +3

Instruction Tuning for Few-Shot Aspect-Based Sentiment Analysis

1 code implementation12 Oct 2022 Siddharth Varia, Shuai Wang, Kishaloy Halder, Robert Vacareanu, Miguel Ballesteros, Yassine Benajiba, Neha Anna John, Rishita Anubhai, Smaranda Muresan, Dan Roth

Aspect-based Sentiment Analysis (ABSA) is a fine-grained sentiment analysis task which involves four elements from user-generated texts: aspect term, aspect category, opinion term, and sentiment polarity.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +2

Cannot find the paper you are looking for? You can Submit a new open access paper.