6 citations · 25 across the 11 of their papers we have counts for
12 papers
Logical Inference for Counting on Semi-structured Tables
Tomoya Kurosawa, Hitomi Yanaka
Recently, the Natural Language Inference (NLI) task has been studied for semi-structured tables that do not have a strict format. Although neural approaches have achieved high perf…
Compositional Semantics and Inference System for Temporal Order based on Japanese CCG
Tomoki Sugimoto, Hitomi Yanaka
Natural Language Inference (NLI) is the task of determining whether a premise entails a hypothesis. NLI with temporal order is a challenging task because tense and aspect are compl…
Building a Video-and-Language Dataset with Human Actions for Multimodal Logical Inference
Riko Suzuki, Hitomi Yanaka, Koji Mineshima +1
This paper introduces a new video-and-language dataset with human actions for multimodal logical inference, which focuses on intentional and aspectual expressions that describe dyn…
Do Grammatical Error Correction Models Realize Grammatical Generalization?
Masato Mita, Hitomi Yanaka
There has been an increased interest in data generation approaches to grammatical error correction (GEC) using pseudo data. However, these approaches suffer from several issues tha…
SyGNS: A Systematic Generalization Testbed Based on Natural Language Semantics
Hitomi Yanaka, Koji Mineshima, Kentaro Inui
Recently, deep neural networks (DNNs) have achieved great success in semantically challenging NLP tasks, yet it remains unclear whether DNN models can capture compositional meaning…
Exploring Transitivity in Neural NLI Models through Veridicality
Hitomi Yanaka, Koji Mineshima, Kentaro Inui
Despite the recent success of deep neural networks in natural language processing, the extent to which they can demonstrate human-like generalization capacities for natural languag…