14.5k citations · 22.4k across the 46 of their papers we have counts for
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Systematic Generalization with Edge Transformers
Leon Bergen, Timothy J. O'Donnell, Dzmitry Bahdanau
Recent research suggests that systematic generalization in natural language understanding remains a challenge for state-of-the-art neural models such as Transformers and Graph Neur…
LAGr: Labeling Aligned Graphs for Improving Systematic Generalization in Semantic Parsing
Dora Jambor, Dzmitry Bahdanau
Semantic parsing is the task of producing a structured meaning representation for natural language utterances or questions. Recent research has pointed out that the commonly-used s…
Compositional Generalization in Dependency Parsing
Emily Goodwin, Siva Reddy, Timothy J. O'Donnell +1
Compositionality -- the ability to combine familiar units like words into novel phrases and sentences -- has been the focus of intense interest in artificial intelligence in recent…
PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models
Torsten Scholak, Nathan Schucher, Dzmitry Bahdanau
Large pre-trained language models for textual data have an unconstrained output space; at each decoding step, they can produce any of 10,000s of sub-word tokens. When fine-tuned to…
Understanding by Understanding Not: Modeling Negation in Language Models
Arian Hosseini, Siva Reddy, Dzmitry Bahdanau +3
Negation is a core construction in natural language. Despite being very successful on many tasks, state-of-the-art pre-trained language models often handle negation incorrectly. To…
Jointly Learning Truth-Conditional Denotations and Groundings using Parallel Attention
Leon Bergen, Dzmitry Bahdanau, Timothy J. O'Donnell
We present a model that jointly learns the denotations of words together with their groundings using a truth-conditional semantics. Our model builds on the neurosymbolic approach o…