Natural Language Processing

Few-shot Learning for Slot Tagging with Attentive Relational Network EACL 2021 Few-shot learning through contextual data augmentation EACL 2021 Few-Shot Named Entity Recognition: An Empirical Baseline Study EMNLP 2021 Few-Shot Novel Concept Learning for Semantic Parsing EMNLP 2021 FewshotQA: A simple framework for few-shot learning of question answering tasks using pre-trained text-to-text models EMNLP 2021 Few-Shot Question Answering by Pretraining Span Selection ACL 2021 Few-Shot Semantic Parsing for New Predicates EACL 2021 Few-Shot Table-to-Text Generation with Prototype Memory EMNLP 2021 Few-Shot Text Classification with Triplet Networks, Data Augmentation, and Curriculum Learning NAACL 2021 Few-Shot Text Generation with Natural Language Instructions EMNLP 2021 Few-Shot Text Ranking with Meta Adapted Synthetic Weak Supervision ACL 2021 FEWS: Large-Scale, Low-Shot Word Sense Disambiguation with the Dictionary EACL 2021 FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation EMNLP 2021 Field Embedding: A Unified Grain-Based Framework for Word Representation NAACL 2021 Fight Fire with Fire: Fine-tuning Hate Detectors using Large Samples of Generated Hate Speech EMNLP 2021 Fighting the COVID-19 Infodemic: Modeling the Perspective of Journalists, Fact-Checkers, Social Media Platforms, Policy Makers, and the Society EMNLP 2021 FII_CROSS at SemEval-2021 Task 2: Multilingual and Cross-lingual Word-in-Context Disambiguation SemEval 2021 Filling the Gap of Utterance-aware and Speaker-aware Representation for Multi-turn Dialogue AAAI 2021 Filling the Gaps in Ancient Akkadian Texts: A Masked Language Modelling Approach EMNLP 2021 FILTER: An Enhanced Fusion Method for Cross-lingual Language Understanding AAAI 2021 Filtered Inner Product Projection for Crosslingual Embedding Alignment ICLR 2021 Financial Opinion Mining EMNLP 2021 Finding a Balanced Degree of Automation for Summary Evaluation EMNLP 2021 Finding BERT’s Idiomatic Key ACL 2021 Finding needles in a haystack: Sampling Structurally-diverse Training Sets from Synthetic Data for Compositional Generalization EMNLP 2021