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Methodology
← Resources & Methods
Natural Language Processing
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Resources & Methods
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Large Language Models
9067 directly classified papers
Papers per year
2010: 1
2013: 1
2017: 1
2018: 14
2019: 129
2020: 336
2021: 463
2022: 582
2023: 1165
2024: 2492
2025: 3325
2026: 558
Papers
Unified Scaling Laws for Routed Language Models
ICML 2022
Self-conditioning Pre-Trained Language Models
ICML 2022
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts
ICML 2022
BERT-Sort: A Zero-shot MLM Semantic Encoder on Ordinal Features for AutoML
AUTOML 2022
Patterns of Text Readability in Human and Predicted Eye Movements
AACL 2022
Cross-domain Analysis on Japanese Legal Pretrained Language Models
AACL 2022
The Effects of Surprisal across Languages: Results from Native and Non-native Reading
AACL 2022
Are Visual-Linguistic Models Commonsense Knowledge Bases?
COLING 2022
PALI-NLP at SemEval-2022 Task 6: iSarcasmEval- Fine-tuning the Pre-trained Model for Detecting Intended Sarcasm
SEMEVAL 2022
stce at SemEval-2022 Task 6: Sarcasm Detection in English Tweets
SEMEVAL 2022
CommunityLM: Probing Partisan Worldviews from Language Models
COLING 2022
Will It Blend? Mixing Training Paradigms & Prompting for Argument Quality Prediction
COLING 2022
Prompting for a conversation: How to control a dialog model?
COLING 2022
DecBERT: Enhancing the Language Understanding of BERT with Causal Attention Masks
NAACL 2022
BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Bangla
NAACL 2022
Empowering parameter-efficient transfer learning by recognizing the kernel structure in self-attention
NAACL 2022
HUE: Pretrained Model and Dataset for Understanding Hanja Documents of Ancient Korea
NAACL 2022
SSN_NLP_MLRG at SemEval-2022 Task 4: Ensemble Learning strategies to detect Patronizing and Condescending Language
NAACL 2022
UMass PCL at SemEval-2022 Task 4: Pre-trained Language Model Ensembles for Detecting Patronizing and Condescending Language
NAACL 2022
ExpertPLM: Pre-training Expert Representation for Expert Finding
EMNLP 2022
Recent Advances in Pre-trained Language Models: Why Do They Work and How Do They Work
AACL 2022
When Cantonese NLP Meets Pre-training: Progress and Challenges
AACL 2022
Reasoning Like Program Executors
EMNLP 2022
Using Commonsense Knowledge to Answer Why-Questions
EMNLP 2022
COST-EFF: Collaborative Optimization of Spatial and Temporal Efficiency with Slenderized Multi-exit Language Models
EMNLP 2022
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