CoLA

Overview edit

Variants: CoLA, CoLA Dev

Associated Benchmarks

This dataset is used in 3 benchmarks:

• Stochastic Optimization - Metrics: Accuracy (max), Accuracy (mean)
• Text Generation - Metrics: acc
• Linguistic Acceptability - Metrics: Accuracy, MCC

Recent Benchmark Submissions

Research Papers

Recent papers with results on this dataset:

• Not all layers are equally as important: Every Layer Counts BERT (2023) -
• LM-CPPF: Paraphrasing-Guided Data Augmentation for Contrastive Prompt-Based Few-Shot Fine-Tuning (2023) -
• Can BERT eat RuCoLA? Topological Data Analysis to Explain (2023) -
• tasksource: A Dataset Harmonization Framework for Streamlined NLP Multi-Task Learning and Evaluation (2023) -
• RuCoLA: Russian Corpus of Linguistic Acceptability (2022) -
• LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale (2022) -
• Acceptability Judgements via Examining the Topology of Attention Maps (2022) -
• data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language (2022) -
• Charformer: Fast Character Transformers via Gradient-based Subword Tokenization (2021) -
• FNet: Mixing Tokens with Fourier Transforms (2021) -
• Entailment as Few-Shot Learner (2021) -
• How to Train BERT with an Academic Budget (2021) -
• CLEAR: Contrastive Learning for Sentence Representation (2020) -
• RealFormer: Transformer Likes Residual Attention (2020) -
• Mixing ADAM and SGD: a Combined Optimization Method (2020) -
• A Statistical Framework for Low-bitwidth Training of Deep Neural Networks (2020) -
• Big Bird: Transformers for Longer Sequences (2020) -
• SqueezeBERT: What can computer vision teach NLP about efficient neural networks? (2020) -
• Learning to Encode Position for Transformer with Continuous Dynamical Model (2020) -
• Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (2019) -