HyperAI

Word Sense Disambiguation On Words In Context

Métriques

Accuracy

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
Accuracy
Paper TitleRepository
GPT-2-XL 1.5B49.8LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions
ST-MoE-L 4.1B (fine-tuned)74ST-MoE: Designing Stable and Transferable Sparse Expert Models-
Hybrid H3 125M (0-shot, rank classification)51.4Hungry Hungry Hippos: Towards Language Modeling with State Space Models
ST-MoE-32B 269B (fine-tuned)77.7ST-MoE: Designing Stable and Transferable Sparse Expert Models-
PaLM 540B (finetuned) 78.8PaLM: Scaling Language Modeling with Pathways
LaMini-GPT 1.5B52.4LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions
RoE-3B52.97Exploring the Benefits of Training Expert Language Models over Instruction Tuning
Sentence LSTM53.1WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representations-
PaLM 2-L (one-shot)66.8PaLM 2 Technical Report
Hybrid H3 125M (3-shot, logit scoring)49.1Hungry Hungry Hippos: Towards Language Modeling with State Space Models
DeConf58.7WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representations-
GPT-3 175B (few-shot, k=32)49.4Language Models are Few-Shot Learners
Vega v2 6B (fine-tuned)77.4Toward Efficient Language Model Pretraining and Downstream Adaptation via Self-Evolution: A Case Study on SuperGLUE-
FLAN-T5-Large 783M64.7LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions
KiC-770M52.40Knowledge-in-Context: Towards Knowledgeable Semi-Parametric Language Models-
ElMo57.7WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representations-
Hybrid H3 125M (0-shot, logit scoring)51.4Hungry Hungry Hippos: Towards Language Modeling with State Space Models
T5-XXL 11B76.9Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
UL2 20B (fine-tuned)77.3UL2: Unifying Language Learning Paradigms
N-Grammer 343M56.1N-Grammer: Augmenting Transformers with latent n-grams
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