ML Research Wiki / Benchmarks / Natural Language Inference / SNLI

SNLI

Natural Language Inference Benchmark

Performance Over Time

📊 Showing 88 results | 📏 Metric: % Test Accuracy

Top Performing Models

Rank Model Paper % Test Accuracy Date Code
1 UnitedSynT5 (3B) 📚 First Train to Generate, then Generate to Train: UnitedSynT5 for Few-Shot NLI 94.70 2024-12-12 -
2 UnitedSynT5 (335M) 📚 First Train to Generate, then Generate to Train: UnitedSynT5 for Few-Shot NLI 93.50 2024-12-12 -
3 Neural Tree Indexers for Text Understanding Entailment as Few-Shot Learner 93.10 2021-04-29 📦 PaddlePaddle/PaddleNLP 📦 sunyilgdx/prompts4keras 📦 cactilab/hateguard
4 EFL (Entailment as Few-shot Learner) + RoBERTa-large Entailment as Few-Shot Learner 93.10 2021-04-29 📦 PaddlePaddle/PaddleNLP 📦 sunyilgdx/prompts4keras 📦 cactilab/hateguard
5 MT-DNN-SMARTLARGEv0 SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization 92.60 2019-11-08 📦 namisan/mt-dnn 📦 microsoft/MT-DNN 📦 archinetai/smart-pytorch
6 RoBERTa-large+Self-Explaining Self-Explaining Structures Improve NLP Models 92.30 2020-12-03 📦 ShannonAI/Self_Explaining_Structures_Improve_NLP_Models
7 RoBERTa-large + self-explaining layer Self-Explaining Structures Improve NLP Models 92.30 2020-12-03 📦 ShannonAI/Self_Explaining_Structures_Improve_NLP_Models
8 CA-MTL Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data 92.10 2020-09-19 📦 CAMTL/CA-MTL
9 SemBERT Semantics-aware BERT for Language Understanding 91.90 2019-09-05 📦 cooelf/SemBERT
10 MT-DNN Multi-Task Deep Neural Networks for Natural Language Understanding 91.60 2019-01-31 📦 namisan/mt-dnn 📦 xycforgithub/MultiTask-MRC 📦 ABaldrati/MT-BERT

All Papers (88)

Semantic Sentence Matching with Densely-connected Recurrent and Co-attentive Information

2018
Densely-Connected Recurrent and Co-Attentive Network Ensemble

Neural Tree Indexers for Text Understanding

2016
300D Full tree matching NTI-SLSTM-LSTM w/ global attention

Sentence Embeddings in NLI with Iterative Refinement Encoders

2018
600D Hierarchical BiLSTM with Max Pooling (HBMP, code)

Semantic Sentence Matching with Densely-connected Recurrent and Co-attentive Information

2018
Densely-Connected Recurrent and Co-Attentive Network (encoder)

Star-Transformer

2019
Star-Transformer (no cross sentence attention)

Order-Embeddings of Images and Language

2015
1024D GRU encoders w/ unsupervised 'skip-thoughts' pre-training