6 citations · 23 across the 44 of their papers we have counts for
6 papers · 1 filter
Lexicosyntactic Inference in Neural Models
Aaron Steven White, Rachel Rudinger, Kyle Rawlins +1
We investigate neural models' ability to capture lexicosyntactic inferences: inferences triggered by the interaction of lexical and syntactic information. We take the task of event…
Hypothesis Only Baselines in Natural Language Inference
Adam Poliak, Jason Naradowsky, Aparajita Haldar +2
We propose a hypothesis only baseline for diagnosing Natural Language Inference (NLI). Especially when an NLI dataset assumes inference is occurring based purely on the relationshi…
Gender Bias in Coreference Resolution
Rachel Rudinger, Jason Naradowsky, Brian Leonard +1
We present an empirical study of gender bias in coreference resolution systems. We first introduce a novel, Winograd schema-style set of minimal pair sentences that differ only by…
Neural models of factuality
Rachel Rudinger, Aaron Steven White, Benjamin Van Durme
We present two neural models for event factuality prediction, which yield significant performance gains over previous models on three event factuality datasets: FactBank, UW, and M…
Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation
Adam Poliak, Aparajita Haldar, Rachel Rudinger +4
We present a large-scale collection of diverse natural language inference (NLI) datasets that help provide insight into how well a sentence representation captures distinct types o…
Neural-Davidsonian Semantic Proto-role Labeling
Rachel Rudinger, Adam Teichert, Ryan Culkin +2
We present a model for semantic proto-role labeling (SPRL) using an adapted bidirectional LSTM encoding strategy that we call "Neural-Davidsonian": predicate-argument structure is…