Papers
BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data
Haoyu Song, Yan Wang, Kaiyan Zhang et al.
Bootstrapped Unsupervised Sentence Representation Learning
Yan Zhang, Ruidan He, Zuozhu Liu et al.
BOUN at SemEval-2021 Task 9: Text Augmentation Techniques for Fact Verification in Tabular Data
Abdullatif Köksal, Yusuf Yüksel, Bekir Yıldırım et al.
Boundary Detection with BERT for Span-level Emotion Cause Analysis
Xiangju Li, Wei Gao, Shi Feng et al.
Box-To-Box Transformations for Modeling Joint Hierarchies
Shib Sankar Dasgupta, Xiang Lorraine Li, Michael Boratko et al.
BreakingBERT@IITK at SemEval-2021 Task 9: Statement Verification and Evidence Finding with Tables
Aditya Jindal, Ankur Gupta, Jaya Srivastava et al.
Breaking Down the Invisible Wall of Informal Fallacies in Online Discussions
Saumya Sahai, Oana Balalau, Roxana Horincar
Breaking Down Walls of Text: How Can NLP Benefit Consumer Privacy?
Abhilasha Ravichander, Alan W Black, Thomas Norton et al.
Bridge-Based Active Domain Adaptation for Aspect Term Extraction
Zhuang Chen, Tieyun Qian
Bridging Subword Gaps in Pretrain-Finetune Paradigm for Natural Language Generation
Xin Liu, Baosong Yang, Dayiheng Liu et al.
Bringing Structure into Summaries: a Faceted Summarization Dataset for Long Scientific Documents
Rui Meng, Khushboo Thaker, Lei Zhang et al.
BTS: Back TranScription for Speech-to-Text Post-Processor using Text-to-Speech-to-Text
Chanjun Park, Jaehyung Seo, Seolhwa Lee et al.
Building Goal-oriented Document-grounded Dialogue Systems
Xi Chen, Faner Lin, Yeju Zhou et al.
C3SL at SemEval-2021 Task 1: Predicting Lexical Complexity of Words in Specific Contexts with Sentence Embeddings
Raul Almeida, Hegler Tissot, Marcos Didonet Del Fabro
CAiRE in DialDoc21: Data Augmentation for Information Seeking Dialogue System
Yan Xu, Etsuko Ishii, Genta Indra Winata et al.
Cambridge at SemEval-2021 Task 1: An Ensemble of Feature-Based and Neural Models for Lexical Complexity Prediction
Zheng Yuan, Gladys Tyen, David Strohmaier
Cambridge at SemEval-2021 Task 2: Neural WiC-Model with Data Augmentation and Exploration of Representation
Zheng Yuan, David Strohmaier
Can Cognate Prediction Be Modelled as a Low-Resource Machine Translation Task?
Clémentine Fourrier, Rachel Bawden, Benoît Sagot
Can Generative Pre-trained Language Models Serve As Knowledge Bases for Closed-book QA?
Cunxiang Wang, Pai Liu, Yue Zhang
Can I Be of Further Assistance? Using Unstructured Knowledge Access to Improve Task-oriented Conversational Modeling
Di Jin, Seokhwan Kim, Dilek Hakkani-Tur
Can Sequence-to-Sequence Models Crack Substitution Ciphers?
Nada Aldarrab, Jonathan May
Can the Transformer Learn Nested Recursion with Symbol Masking?
Jean-Philippe Bernardy, Adam Ek, Vladislav Maraev
Can Transformer Language Models Predict Psychometric Properties?
Antonio Laverghetta Jr., Animesh Nighojkar, Jamshidbek Mirzakhalov et al.
Can Transformer Models Measure Coherence In Text: Re-Thinking the Shuffle Test
Philippe Laban, Luke Dai, Lucas Bandarkar et al.
Can vectors read minds better than experts? Comparing data augmentation strategies for the automated scoring of children’s mindreading ability
Venelin Kovatchev, Phillip Smith, Mark Lee et al.