no code implementations • ACL 2022 • Jiawei Zhou, Jason Eisner, Michael Newman, Emmanouil Antonios Platanios, Sam Thomson
Standard conversational semantic parsing maps a complete user utterance into an executable program, after which the program is executed to respond to the user.
no code implementations • ACL 2022 • Anton Belyy, Chieh-Yang Huang, Jacob Andreas, Emmanouil Antonios Platanios, Sam Thomson, Richard Shin, Subhro Roy, Aleksandr Nisnevich, Charles Chen, Benjamin Van Durme
Collecting data for conversational semantic parsing is a time-consuming and demanding process.
no code implementations • 8 Jul 2023 • Belinda Z. Li, Jason Eisner, Adam Pauls, Sam Thomson
Voice dictation is an increasingly important text input modality.
1 code implementation • NeurIPS 2023 • Subhro Roy, Sam Thomson, Tongfei Chen, Richard Shin, Adam Pauls, Jason Eisner, Benjamin Van Durme
We introduce BenchCLAMP, a Benchmark to evaluate Constrained LAnguage Model Parsing, that includes context-free grammars for seven semantic parsing datasets and two syntactic parsing datasets with varied output representations, as well as a constrained decoding interface to generate only valid outputs covered by these grammars.
1 code implementation • 24 May 2022 • Elias Stengel-Eskin, Emmanouil Antonios Platanios, Adam Pauls, Sam Thomson, Hao Fang, Benjamin Van Durme, Jason Eisner, Yu Su
Rejecting class imbalance as the sole culprit, we reveal that the trend is closely associated with an effect we call source signal dilution, where strong lexical cues for the new symbol become diluted as the training dataset grows.
no code implementations • ACL 2021 • Emmanouil Antonios Platanios, Adam Pauls, Subhro Roy, Yuchen Zhang, Alexander Kyte, Alan Guo, Sam Thomson, Jayant Krishnamurthy, Jason Wolfe, Jacob Andreas, Dan Klein
Conversational semantic parsers map user utterances to executable programs given dialogue histories composed of previous utterances, programs, and system responses.
no code implementations • NAACL 2021 • Pengcheng Yin, Hao Fang, Graham Neubig, Adam Pauls, Emmanouil Antonios Platanios, Yu Su, Sam Thomson, Jacob Andreas
We describe a span-level supervised attention loss that improves compositional generalization in semantic parsers.
1 code implementation • EMNLP 2021 • Richard Shin, Christopher H. Lin, Sam Thomson, Charles Chen, Subhro Roy, Emmanouil Antonios Platanios, Adam Pauls, Dan Klein, Jason Eisner, Benjamin Van Durme
We explore the use of large pretrained language models as few-shot semantic parsers.
1 code implementation • 24 Sep 2020 • Semantic Machines, Jacob Andreas, John Bufe, David Burkett, Charles Chen, Josh Clausman, Jean Crawford, Kate Crim, Jordan DeLoach, Leah Dorner, Jason Eisner, Hao Fang, Alan Guo, David Hall, Kristin Hayes, Kellie Hill, Diana Ho, Wendy Iwaszuk, Smriti Jha, Dan Klein, Jayant Krishnamurthy, Theo Lanman, Percy Liang, Christopher H Lin, Ilya Lintsbakh, Andy McGovern, Aleksandr Nisnevich, Adam Pauls, Dmitrij Petters, Brent Read, Dan Roth, Subhro Roy, Jesse Rusak, Beth Short, Div Slomin, Ben Snyder, Stephon Striplin, Yu Su, Zachary Tellman, Sam Thomson, Andrei Vorobev, Izabela Witoszko, Jason Wolfe, Abby Wray, Yuchen Zhang, Alexander Zotov
We describe an approach to task-oriented dialogue in which dialogue state is represented as a dataflow graph.
1 code implementation • EMNLP 2018 • Swabha Swayamdipta, Sam Thomson, Kenton Lee, Luke Zettlemoyer, Chris Dyer, Noah A. Smith
We introduce the syntactic scaffold, an approach to incorporating syntactic information into semantic tasks.
1 code implementation • EMNLP 2018 • Hao Peng, Roy Schwartz, Sam Thomson, Noah A. Smith
We characterize this connection formally, defining rational recurrences to be recurrent hidden state update functions that can be written as the Forward calculation of a finite set of WFSAs.
no code implementations • ACL 2018 • Roy Schwartz, Sam Thomson, Noah A. Smith
Recurrent and convolutional neural networks comprise two distinct families of models that have proven to be useful for encoding natural language utterances.
1 code implementation • HLT 2015 • Fei Liu, Jeffrey Flanigan, Sam Thomson, Norman Sadeh, Noah A. Smith
We present a novel abstractive summarization framework that draws on the recent development of a treebank for the Abstract Meaning Representation (AMR).
2 code implementations • 15 May 2018 • Roy Schwartz, Sam Thomson, Noah A. Smith
Recurrent and convolutional neural networks comprise two distinct families of models that have proven to be useful for encoding natural language utterances.
Explainable artificial intelligence General Classification +3
1 code implementation • ACL 2018 • Hao Peng, Sam Thomson, Noah A. Smith
We introduce the structured projection of intermediate gradients optimization technique (SPIGOT), a new method for backpropagating through neural networks that include hard-decision structured predictions (e. g., parsing) in intermediate layers.
2 code implementations • NAACL 2018 • Hao Peng, Sam Thomson, Swabha Swayamdipta, Noah A. Smith
We present a new approach to learning semantic parsers from multiple datasets, even when the target semantic formalisms are drastically different, and the underlying corpora do not overlap.
7 code implementations • CVPR 2018 • Rowan Zellers, Mark Yatskar, Sam Thomson, Yejin Choi
We then introduce Stacked Motif Networks, a new architecture designed to capture higher order motifs in scene graphs that further improves over our strong baseline by an average 7. 1% relative gain.
Ranked #8 on Panoptic Scene Graph Generation on PSG Dataset
10 code implementations • 29 Jun 2017 • Swabha Swayamdipta, Sam Thomson, Chris Dyer, Noah A. Smith
We present a new, efficient frame-semantic parser that labels semantic arguments to FrameNet predicates.
1 code implementation • ACL 2017 • Hao Peng, Sam Thomson, Noah A. Smith
We present a deep neural architecture that parses sentences into three semantic dependency graph formalisms.