Metrics also Disagree in the Low Scoring Range: Revisiting Summarization Evaluation Metrics

no code implementations • COLING 2020 • Manik Bhandari, Pranav Gour, Atabak Ashfaq, PengFei Liu

In text summarization, evaluating the efficacy of automatic metrics without human judgments has become recently popular.

Text Summarization

Re-evaluating Evaluation in Text Summarization

1 code implementation • EMNLP 2020 • Manik Bhandari, Pranav Gour, Atabak Ashfaq, PengFei Liu, Graham Neubig

Automated evaluation metrics as a stand-in for manual evaluation are an essential part of the development of text-generation tasks such as text summarization.

Text Generation Text Summarization

Confidence-based Graph Convolutional Networks for Semi-Supervised Learning

1 code implementation • 24 Jan 2019 • Shikhar Vashishth, Prateek Yadav, Manik Bhandari, Partha Talukdar

Graph-based Semi-Supervised Learning (SSL) methods aim to address this problem by labeling a small subset of the nodes as seeds and then utilizing the graph structure to predict label scores for the rest of the nodes in the graph.

Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks

1 code implementation • ACL 2019 • Shikhar Vashishth, Manik Bhandari, Prateek Yadav, Piyush Rai, Chiranjib Bhattacharyya, Partha Talukdar

Word embeddings have been widely adopted across several NLP applications.

Learning Word Embeddings