https://github.com/safakkbilici/Academic-Paper-Title-Recommendation
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Papers with Code 아카이브
Question Answering
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
- 153
- 보존된 평가 기록
- 1,781
Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.
( Image credit: SQuAD )
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/sagorbrur/bangla-bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/sagorbrur/codeswitch
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/sahilkhose/FloodNet
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding
https://github.com/sahilkhose/floodnet_vqa
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding
https://github.com/sahsaeedi/triple-preference-optimization
Insights into Alignment: Evaluating DPO and its Variants Across Multiple Tasks
https://github.com/sajadalipour7/persian-grapheme-to-phoneme-with-transformer
https://github.com/sajjjadayobi/ParsBigBird
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/salanueva/UniVSE
Evaluating Multimodal Representations on Visual Semantic Textual Similarity
https://github.com/salesforce/GeDi
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/salesforce/codet5
https://github.com/salrowili/biom-transformers
Transferability of Natural Language Inference to Biomedical Question Answering
https://github.com/sambanova/generative_data_prep
https://github.com/sambanova/lm-evaluation-harness
https://github.com/samirsahoo007/Audio-and-Speech-Processing
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/samrelins/tanda_search_qa_tool
TANDA: Transfer and Adapt Pre-Trained Transformer Models for Answer Sentence Selection
https://github.com/samsam3232/qampari
https://github.com/samwisegamjeee/pytorch-transformers
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/samyakjain0112/Video-denoising_tensorflow-core-api-2.0
https://github.com/sangyx/gtrick/tree/main/benchmark/pyg
Robust Optimization as Data Augmentation for Large-scale Graphs
https://github.com/saparina/text2sql-nlvariation
https://github.com/sarahesl/pubmedclip
Overcoming Data Limitation in Medical Visual Question Answering
https://github.com/saraswat/munkhdalai-nse
https://github.com/saravanakumarjsk/BERT-collection
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/sarthaxxxxx/Attention-is-all-you-need
https://github.com/sarveshsparab/DeepElmoEmbedNer
https://github.com/satyajitghana/TSAI-DeepNLP-END2.0
https://github.com/saurabhkulkarni77/BERT_multilabel
https://github.com/saurabhnlp/bert
https://github.com/sauram/Machine-Translation-using-Attention-Model
https://github.com/sayakbanerjee1999/Chat-Bot
Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks
https://github.com/sayakpaul/swin-transformers-tf
https://github.com/sayef/fsner
https://github.com/sberbank-ai/ner-bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/scakc/QAwiki
Ask Me Anything: Dynamic Memory Networks for Natural Language Processing
https://github.com/schenliu/longformer-chinese
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.