114 citations · 355 across the 20 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
cs.LG2020★ 1 cited
Efficient Estimation of Influence of a Training Instance
Sosuke Kobayashi, Sho Yokoi, Jun Suzuki +1
Understanding the influence of a training instance on a neural network model leads to improving interpretability. However, it is difficult and inefficient to evaluate the influence…
cs.CL2020★ 4 cited
Instance-Based Learning of Span Representations: A Case Study through Named Entity Recognition
Hiroki Ouchi, Jun Suzuki, Sosuke Kobayashi +4
Interpretable rationales for model predictions play a critical role in practical applications. In this study, we develop models possessing interpretable inference process for struc…
cs.CL2020
All Word Embeddings from One Embedding
Sho Takase, Sosuke Kobayashi
In neural network-based models for natural language processing (NLP), the largest part of the parameters often consists of word embeddings. Conventional models prepare a large embe…