Ramesh Nallapati

Embedding-based Zero-shot Retrieval through Query Generation

2020 · arXiv (Cornell University)

Passage retrieval addresses the problem of locating relevant passages, usually from a large corpus, given a query. In practice, lexical term-matching algorithms like BM25 are popular choices for retrieval owing to their efficiency. However, term-based …

Retrieval, Re-ranking and Multi-task Learning for Knowledge-Base Question Answering

2021

Question answering over knowledge bases (KBQA) usually involves three sub-tasks, namely topic entity detection, entity linking and relation detection. Due to the large number of entities and relations inside knowledge bases (KB), previous work usually …

Entity-level Factual Consistency of Abstractive Text Summarization

2021

Feng Nan, Ramesh Nallapati, Zhiguo Wang, Cicero Nogueira dos Santos, Henghui Zhu, Dejiao Zhang, Kathleen McKeown, Bing Xiang. Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume. …

Pointing the Unknown Words

2016 · arXiv (Cornell University)

The problem of rare and unknown words is an important issue that can potentially influence the performance of many NLP systems, including both the traditional count-based and the deep learning models. We propose a novel …

SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents

2016 · arXiv (Cornell University)

We present SummaRuNNer, a Recurrent Neural Network (RNN) based sequence model for extractive summarization of documents and show that it achieves performance better than or comparable to state-of-the-art. Our model has the additional advantage of …

SummaRuNNer: A Recurrent Neural Network Based Sequence Model for Extractive Summarization of Documents

2017 · Proceedings of the AAAI Conference on Artificial Intelligence

We present SummaRuNNer, a Recurrent Neural Network (RNN) based sequence model for extractive summarization of documents and show that it achieves performance better than or comparable to state-of-the-art. Our model has the additional advantage of …

Multi-passage BERT: A Globally Normalized BERT Model for Open-domain Question Answering

2019

Zhiguo Wang, Patrick Ng, Xiaofei Ma, Ramesh Nallapati, Bing Xiang. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019.

Universal Text Representation from BERT: An Empirical Study

2019 · arXiv (Cornell University)

We present a systematic investigation of layer-wise BERT activations for general-purpose text representations to understand what linguistic information they capture and how transferable they are across different tasks. Sentence-level embeddings are evaluated against two state-of-the-art …

Supporting Clustering with Contrastive Learning

2021

Dejiao Zhang, Feng Nan, Xiaokai Wei, Shang-Wen Li, Henghui Zhu, Kathleen McKeown, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang. Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: …