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Natural Language Inference

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Natural language inference (NLI) is the task of determining whether a "hypothesis" is true (entailment), false (contradiction), or undetermined (neutral) given a "premise".

Example:

Premise	Label	Hypothesis
A man inspects the uniform of a figure in some East Asian country.	contradiction	The man is sleeping.
An older and younger man smiling.	neutral	Two men are smiling and laughing at the cats playing on the floor.
A soccer game with multiple males playing.	entailment	Some men are playing a sport.

Approaches used for NLI include earlier symbolic and statistical approaches to more recent deep learning approaches. Benchmark datasets used for NLI include SNLI, MultiNLI, SciTail, among others. You can get hands-on practice on the SNLI task by following this d2l.ai chapter.

Further readings:

Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/ibm/vira-intent-discovery

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/icewing1996/bert_dep

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/idc-dsi/Arapet

Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference

https://github.com/idiotprofessorchen/bert.github.io

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/iesl/geometric_graph_embedding

Order-Embeddings of Images and Language

https://github.com/iflytek/cino

KLUE: Korean Language Understanding Evaluation

https://github.com/ilhamfp/indonesian-text-classification-multilingual

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/iliaschalkidis/ELMo-keras

Deep contextualized word representations

https://github.com/imamathcat/LASER_Dependencies

Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond

https://github.com/imgarylai/bert-embedding

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/imran3180/pytorch-nli

GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

https://github.com/insait-institute/lm-evaluation-harness-bg

Language Models are Few-Shot Learners

https://github.com/intel/intel-extension-for-transformers

Prune Once for All: Sparse Pre-Trained Language Models

https://github.com/itaigat/removing-bias-in-multi-modal-classifiers

Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases

https://github.com/itay1itzhak/instructedtobias

Language models show human-like content effects on reasoning tasks

https://github.com/itsShnik/adaptively-finetuning-transformers

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/itspreeti25/Q-A-implementation-using-BERT-finetuned-on-multiple-datasets

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/itzprashu1/prashant

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

https://github.com/ivendrov/order-embedding

Order-Embeddings of Images and Language

https://github.com/jadore801120/attention-is-all-you-need-pytorch

A Structured Self-attentive Sentence Embedding

https://github.com/jageshmaharjan/BERT_Service

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/jaketae/fnet

FNet: Mixing Tokens with Fourier Transforms

https://github.com/jaketae/g-mlp

Pay Attention to MLPs

https://github.com/jaketae/pytorch-malware-detection

DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

https://github.com/jaketae/realformer

RealFormer: Transformer Likes Residual Attention

https://github.com/jangjoongkeon/JK

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/jastfkjg/semantic-matching

ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs

https://github.com/jbdel/vilmedic

Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation

https://github.com/jean-kunz/ml_research_papers

Supervised Learning of Universal Sentence Representations from Natural Language Inference Data

https://github.com/jellyfish042/rwkv-statetuning

AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts

https://github.com/jeongukjae/KR-BERT-SimCSE

KorNLI and KorSTS: New Benchmark Datasets for Korean Natural Language Understanding

https://github.com/jeongukjae/smaller-labse

Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond

https://github.com/jgc128/mednli

Lessons from Natural Language Inference in the Clinical Domain

https://github.com/jgc128/mednli_baseline

Lessons from Natural Language Inference in the Clinical Domain

https://github.com/jiacheng-xu/text-sum-uncertainty

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

https://github.com/jiamingkong/infoxlm_paddle

Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond

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