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2020 – today
- 2022
[c15]Riku Arakawa, Hiromu Yakura, Sosuke Kobayashi:
VocabEncounter: NMT-powered Vocabulary Learning by Presenting Computer-Generated Usages of Foreign Words into Users' Daily Lives. CHI 2022: 6:1-6:21- [c14]Sosuke Kobayashi, Eiichi Matsumoto, Vincent Sitzmann:
Decomposing NeRF for Editing via Feature Field Distillation. NeurIPS 2022 - [i16]Sosuke Kobayashi, Shun Kiyono, Jun Suzuki, Kentaro Inui:
Diverse Lottery Tickets Boost Ensemble from a Single Pretrained Model. CoRR abs/2205.11833 (2022) - [i15]Sosuke Kobayashi, Eiichi Matsumoto, Vincent Sitzmann:
Decomposing NeRF for Editing via Feature Field Distillation. CoRR abs/2205.15585 (2022) - [i14]Sho Takase, Shun Kiyono, Sosuke Kobayashi, Jun Suzuki:
On Layer Normalizations and Residual Connections in Transformers. CoRR abs/2206.00330 (2022) - 2021
- [j2]Hiroki Ouchi, Jun Suzuki, Sosuke Kobayashi, Sho Yokoi, Tatsuki Kuribayashi, Masashi Yoshikawa, Kentaro Inui:
Instance-Based Neural Dependency Parsing. Trans. Assoc. Comput. Linguistics 9: 1493-1507 (2021) - [c13]Shun Kiyono, Sosuke Kobayashi, Jun Suzuki, Kentaro Inui:
SHAPE : Shifted Absolute Position Embedding for Transformers. EMNLP (1) 2021: 3309-3321 - [i13]Shun Kiyono, Sosuke Kobayashi, Jun Suzuki, Kentaro Inui:
SHAPE: Shifted Absolute Position Embedding for Transformers. CoRR abs/2109.05644 (2021) - [i12]Hiroki Ouchi, Jun Suzuki, Sosuke Kobayashi, Sho Yokoi, Tatsuki Kuribayashi, Masashi Yoshikawa, Kentaro Inui:
Instance-Based Neural Dependency Parsing. CoRR abs/2109.13497 (2021) - 2020
- [j1]Masaki Saito
, Shunta Saito, Masanori Koyama, Sosuke Kobayashi:
Train Sparsely, Generate Densely: Memory-Efficient Unsupervised Training of High-Resolution Temporal GAN. Int. J. Comput. Vis. 128(10): 2586-2606 (2020) - [c12]Hiroki Ouchi, Jun Suzuki, Sosuke Kobayashi, Sho Yokoi, Tatsuki Kuribayashi, Ryuto Konno, Kentaro Inui:
Instance-Based Learning of Span Representations: A Case Study through Named Entity Recognition. ACL 2020: 6452-6459 - [c11]Sosuke Kobayashi, Sho Yokoi, Jun Suzuki, Kentaro Inui:
Efficient Estimation of Influence of a Training Instance. SustaiNLP@EMNLP 2020: 41-47 - [c10]Sho Takase, Sosuke Kobayashi:
All Word Embeddings from One Embedding. NeurIPS 2020 - [i11]Sho Takase, Sosuke Kobayashi:
All Word Embeddings from One Embedding. CoRR abs/2004.12073 (2020) - [i10]Hiroki Ouchi, Jun Suzuki, Sosuke Kobayashi, Sho Yokoi, Tatsuki Kuribayashi, Ryuto Konno, Kentaro Inui:
Instance-Based Learning of Span Representations: A Case Study through Named Entity Recognition. CoRR abs/2004.14514 (2020) - [i9]Sosuke Kobayashi, Sho Yokoi, Jun Suzuki, Kentaro Inui:
Efficient Estimation of Influence of a Training Instance. CoRR abs/2012.04207 (2020)
2010 – 2019
- 2019
- [i8]Tsu-Jui Fu, Yuta Tsuboi, Sosuke Kobayashi, Yuta Kikuchi:
Learning from Observation-Only Demonstration for Task-Oriented Language Grounding via Self-Examination. ViGIL@NeurIPS 2019 - [i7]Takuya Shimada, Shoichiro Yamaguchi, Kohei Hayashi, Sosuke Kobayashi:
Data Interpolating Prediction: Alternative Interpretation of Mixup. CoRR abs/1906.08412 (2019) - 2018
- [c9]Reina Akama, Kento Watanabe, Sho Yokoi, Sosuke Kobayashi, Kentaro Inui:
Unsupervised Learning of Style-sensitive Word Vectors. ACL (2) 2018: 572-578 - [c8]Sho Yokoi, Sosuke Kobayashi, Kenji Fukumizu, Jun Suzuki, Kentaro Inui:
Pointwise HSIC: A Linear-Time Kernelized Co-occurrence Norm for Sparse Linguistic Expressions. EMNLP 2018: 1763-1775 - [c7]Jun Hatori, Yuta Kikuchi, Sosuke Kobayashi, Kuniyuki Takahashi, Yuta Tsuboi, Yuya Unno, Wilson Ko, Jethro Tan:
Interactively Picking Real-World Objects with Unconstrained Spoken Language Instructions. ICRA 2018: 3774-3781 - [c6]Sosuke Kobayashi:
Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relations. NAACL-HLT (2) 2018: 452-457 - [i6]Reina Akama, Kento Watanabe, Sho Yokoi, Sosuke Kobayashi, Kentaro Inui:
Unsupervised Learning of Style-sensitive Word Vectors. CoRR abs/1805.05581 (2018) - [i5]Sosuke Kobayashi:
Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relations. CoRR abs/1805.06201 (2018) - [i4]Sho Yokoi, Sosuke Kobayashi, Kenji Fukumizu, Jun Suzuki, Kentaro Inui:
Pointwise HSIC: A Linear-Time Kernelized Co-occurrence Norm for Sparse Linguistic Expressions. CoRR abs/1809.00800 (2018) - [i3]Riku Arakawa, Sosuke Kobayashi, Yuya Unno, Yuta Tsuboi, Shin-ichi Maeda:
DQN-TAMER: Human-in-the-Loop Reinforcement Learning with Intractable Feedback. CoRR abs/1810.11748 (2018) - 2017
- [c5]Melissa Roemmele, Sosuke Kobayashi, Naoya Inoue, Andrew Gordon:
An RNN-based Binary Classifier for the Story Cloze Test. LSDSem@EACL 2017: 74-80 - [c4]Reina Akama, Kazuaki Inada, Naoya Inoue, Sosuke Kobayashi, Kentaro Inui:
Generating Stylistically Consistent Dialog Responses with Transfer Learning. IJCNLP(2) 2017: 408-412 - [c3]Sosuke Kobayashi, Naoaki Okazaki, Kentaro Inui:
A Neural Language Model for Dynamically Representing the Meanings of Unknown Words and Entities in a Discourse. IJCNLP(1) 2017: 473-483 - [i2]Sosuke Kobayashi, Naoaki Okazaki, Kentaro Inui:
A Neural Language Model for Dynamically Representing the Meanings of Unknown Words and Entities in a Discourse. CoRR abs/1709.01679 (2017) - [i1]Jun Hatori, Yuta Kikuchi, Sosuke Kobayashi, Kuniyuki Takahashi, Yuta Tsuboi, Yuya Unno, Wilson Ko, Jethro Tan:
Interactively Picking Real-World Objects with Unconstrained Spoken Language Instructions. CoRR abs/1710.06280 (2017) - 2016
- [c2]Sosuke Kobayashi, Ran Tian, Naoaki Okazaki, Kentaro Inui:
Dynamic Entity Representation with Max-pooling Improves Machine Reading. HLT-NAACL 2016: 850-855 - [c1]Yuki Igarashi, Hiroya Komatsu, Sosuke Kobayashi, Naoaki Okazaki, Kentaro Inui:
Tohoku at SemEval-2016 Task 6: Feature-based Model versus Convolutional Neural Network for Stance Detection. SemEval@NAACL-HLT 2016: 401-407
Coauthor Index
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last updated on 2023-05-13 04:02 CEST by the dblp team
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