Semih Yavuz

Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset

2019

Bill Byrne, Karthik Krishnamoorthi, Chinnadhurai Sankar, Arvind Neelakantan, Ben Goodrich, Daniel Duckworth, Semih Yavuz, Amit Dubey, Kyu-Young Kim, Andy Cedilnik. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th …

Modeling Multi-hop Question Answering as Single Sequence Prediction

2022 · arXiv (Cornell University)

Fusion-in-decoder (Fid) (Izacard and Grave, 2020) is a generative question answering (QA) model that leverages passage retrieval with a pre-trained transformer and pushed the state of the art on single-hop QA. However, the complexity of …

Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

2019 · arXiv (Cornell University)

Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models. Lingvo models are composed of modular building blocks that are flexible and easily extensible, …

RNG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering

2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Existing KBQA approaches, despite achieving strong performance on i.i.d. test data, often struggle in generalizing to questions involving unseen KB schema items. Prior rankingbased approaches have shown some success in generalization, but suffer from the …