2 code implementations • EMNLP 2018 • Lisa Bauer, Yicheng Wang, Mohit Bansal
We instead focus on a more challenging multi-hop generative task (NarrativeQA), which requires the model to reason, gather, and synthesize disjoint pieces of information within the context to generate an answer.
Ranked #6 on Question Answering on NarrativeQA
1 code implementation • EMNLP 2021 • Swarnadeep Saha, Prateek Yadav, Lisa Bauer, Mohit Bansal
Recent commonsense-reasoning tasks are typically discriminative in nature, where a model answers a multiple-choice question for a certain context.
1 code implementation • EACL 2021 • Lisa Bauer, Mohit Bansal
For knowledge integration to yield peak performance, it is critical to select a knowledge graph (KG) that is well-aligned with the given task's objective.
no code implementations • WS 2020 • Yixin Nie, Lisa Bauer, Mohit Bansal
Automatic fact checking is an important task motivated by the need for detecting and preventing the spread of misinformation across the web.
no code implementations • Joint Conference on Lexical and Computational Semantics 2021 • Duccio Pappadopulo, Lisa Bauer, Marco Farina, Ozan İrsoy, Mohit Bansal
In this paper, we apply DAG-LSTMs to the conversation disentanglement task.
no code implementations • NAACL (DeeLIO) 2021 • Lisa Bauer, Lingjia Deng, Mohit Bansal
We examine the effect of domain-specific external knowledge variations on deep large scale language model performance.
no code implementations • 16 Dec 2021 • Lisa Bauer, Karthik Gopalakrishnan, Spandana Gella, Yang Liu, Mohit Bansal, Dilek Hakkani-Tur
We define three broad classes of task descriptions for these tasks: statement, question, and completion, with numerous lexical variants within each class.