RTE

Overview edit

Variants: RTE

Associated Benchmarks

This dataset is used in 2 benchmarks:

• Natural Language Inference - Metrics: Accuracy
• Classification - Metrics: Test Accuracy

Recent Benchmark Submissions

Research Papers

Recent papers with results on this dataset:

• Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization (2024) -
• Not all layers are equally as important: Every Layer Counts BERT (2023) -
• The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning (2023) -
• PaLM 2 Technical Report (2023) -
• LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions (2023) -
• BloombergGPT: A Large Language Model for Finance (2023) -
• Exploring the Benefits of Training Expert Language Models over Instruction Tuning (2023) -
• Hungry Hungry Hippos: Towards Language Modeling with State Space Models (2022) -
• OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization (2022) -
• Toward Efficient Language Model Pretraining and Downstream Adaptation via Self-Evolution: A Case Study on SuperGLUE (2022) -
• Knowledge-in-Context: Towards Knowledgeable Semi-Parametric Language Models (2022) -
• Guess the Instruction! Flipped Learning Makes Language Models Stronger Zero-Shot Learners (2022) -
• Ask Me Anything: A simple strategy for prompting language models (2022) -
• LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale (2022) -
• AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model (2022) -
• N-Grammer: Augmenting Transformers with latent n-grams (2022) -
• UL2: Unifying Language Learning Paradigms (2022) -
• PaLM: Scaling Language Modeling with Pathways (2022) -
• ST-MoE: Designing Stable and Transferable Sparse Expert Models (2022) -
• data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language (2022) -