Papers with Code 아카이브
Common Sense Reasoning
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
- 24
- 보존된 평가 기록
- 397
Common sense reasoning tasks are intended to require the model to go beyond pattern recognition. Instead, the model should use "common sense" or world knowledge to make inferences.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/lucidrains/PaLM-jax
https://github.com/lucidrains/PaLM-pytorch
https://github.com/lucidrains/compressive-transformer-pytorch
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
https://github.com/lucidrains/routing-transformer
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
https://github.com/lucidrains/sinkhorn-transformer
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
https://github.com/luckynozomi/PPI_Bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/lukemelas/PyTorch-Pretrained-ViT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/luomancs/retriever_reader_for_okvqa
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/luozhilin99/bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/lupantech/chameleon-llm
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
https://github.com/lvyufeng/Cybertron/blob/master/cybertron/models/bert.py
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/lvyufeng/bert4ms
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/lvyufeng/mindspore-nlp-tutorial
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/lyccol/CodeBERT-based-webshell-detection
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/lyqcom/albert
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
https://github.com/macournoyer/neuralconvo
https://github.com/madhawav/MML
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/maknotavailable/pytorch-pretrained-bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/mandubian/codenets
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
https://github.com/manideep2510/siamese-BERT-fake-news-detection-LIAR
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/manshri/tesum
mT5: A massively multilingual pre-trained text-to-text transformer
https://github.com/manthan2305/Efficient-G-Retriever
G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering
https://github.com/maxudong1993/mybert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/mayurnewase/Quora-Bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/mbforbes/physical-commonsense
Do Neural Language Representations Learn Physical Commonsense?
https://github.com/mbzuai-clear/ioe-prompting
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
https://github.com/mbzuai-paris/lm-evaluation-harness-atlas-chat
https://github.com/meelfy/pytorch_pretrained_bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/meizi1114/bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/meta-llama/llama
https://github.com/metalbubble/TRN-pytorch
https://github.com/mevius6/smallgan
Image Generation From Small Datasets via Batch Statistics Adaptation
https://github.com/mgmalek/efficient_cross_entropy
https://github.com/mhaseeb123/DeepMSim
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/mhazoglou/PVM_PyCUDA
Unsupervised Learning from Continuous Video in a Scalable Predictive Recurrent Network
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.