168 citations · 646 across the 40 of their papers we have counts for
8 papers · 2 filters
Enforcing Consistency in Weakly Supervised Semantic Parsing
Nitish Gupta, Sameer Singh, Matt Gardner
The predominant challenge in weakly supervised semantic parsing is that of spurious programs that evaluate to correct answers for the wrong reasons. Prior work uses elaborate searc…
Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models
Robert L. Logan, Ivana Balažević, Eric Wallace +3
Prompting language models (LMs) with training examples and task descriptions has been seen as critical to recent successes in few-shot learning. In this work, we show that finetuni…
Evaluating Entity Disambiguation and the Role of Popularity in Retrieval-Based NLP
Anthony Chen, Pallavi Gudipati, Shayne Longpre +2
Retrieval is a core component for open-domain NLP tasks. In open-domain tasks, multiple entities can share a name, making disambiguation an inherent yet under-explored problem. We…
Generative Context Pair Selection for Multi-hop Question Answering
Dheeru Dua, Cicero Nogueira dos Santos, Patrick Ng +4
Compositional reasoning tasks like multi-hop question answering, require making latent decisions to get the final answer, given a question. However, crowdsourced datasets often cap…
Learning with Instance Bundles for Reading Comprehension
Dheeru Dua, Pradeep Dasigi, Sameer Singh +1
When training most modern reading comprehension models, all the questions associated with a context are treated as being independent from each other. However, closely related quest…
An Empirical Comparison of Instance Attribution Methods for NLP
Pouya Pezeshkpour, Sarthak Jain, Byron C. Wallace +1
Widespread adoption of deep models has motivated a pressing need for approaches to interpret network outputs and to facilitate model debugging. Instance attribution methods constit…