Papers with Code 아카이브
Common Sense Reasoning
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 17
- 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/jungomi/swiss-language-model
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/junhahyung/bert_finetune
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/junhahyung/bert_transfer
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/junnyu/paddle_t5
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/jzhang38/tinyllama
Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling
https://github.com/kamalkraj/ALBERT-TF2.0
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
https://github.com/kamalkraj/BERT-SQuAD
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/kamalkraj/BERT_NER
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/kamanphoebe/look-into-moes
https://github.com/karenacorn99/explore-bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/karpathy/build-nanogpt
https://github.com/karpathy/llama2.c
https://github.com/karpathy/llm.c
https://github.com/karta282950/bert-multiclass
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/karthikv792/gpt-plan-benchmark
https://github.com/kaushaltrivedi/fast-bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/kaviezhang/meshmamba
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
https://github.com/kayvr/token-hawk
https://github.com/kbressem/longhealth
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
https://github.com/kbressem/medalpaca
https://github.com/keiyamashita111/aaproject
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/kelly2016/multi-label-bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/khalidsaifullaah/bertify
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/khfs/DuplexMamba
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
https://github.com/kiko441500/google_bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/kingcheng2000/bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/kingcong/gpu_albert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/kinimod23/NMT_Project
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/knowlab/bi-weekly-paper-presentation
https://github.com/knuddj1/op_text
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/knuddy/op_text
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/kobowon/cs470_project_version2
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/koustuvsinha/clutrr-workshop
Compositional Language Understanding with Text-based Relational Reasoning
https://github.com/kpe/bert-for-tf2
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/kpot/keras-transformer
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.