https://github.com/mia-workshop/mia-shared-task-2022
MKQA: A Linguistically Diverse Benchmark for Multilingual Open Domain Question Answering
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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/nidhikamal-emb/DPR_repo
Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering
https://github.com/openmatch/coco-dr
https://github.com/princeton-nlp/DensePhrases
Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering
https://github.com/princeton-nlp/helmet
https://github.com/rvlopes/gloria
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
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/saparina/text2sql-nlvariation
Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness
https://github.com/see--/natural-question-answering
https://github.com/shmsw25/GraphRetriever
Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering
https://github.com/thakur-nandan/beir-colbert
https://github.com/thunlp/clueanchor
Atlas: Few-shot Learning with Retrieval Augmented Language Models
https://github.com/uclnlp/APE
Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering
https://github.com/xfactlab/emnlp2023-damaging-retrieval
Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering
https://github.com/xinyadu/rgqa
https://github.com/xuefuzhao/openmoe
ST-MoE: Designing Stable and Transferable Sparse Expert Models
https://github.com/yikangshen/megablocks
ST-MoE: Designing Stable and Transferable Sparse Expert Models
https://github.com/zhaoyuesun/phee
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.