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TriviaQA

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

https://github.com/hltcoe/colbert-x

Relevance-guided Supervision for OpenQA with ColBERT

https://github.com/hongyuntw/DPR

Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering

https://github.com/hongyuntw/DPR_BESS

Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering

https://github.com/huggingface/transformers

Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering

https://github.com/hyintell/retrievalqa

TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

https://github.com/iinemo/lm-polygraph

Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback

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

Longformer: The Long-Document Transformer

https://github.com/jhyuklee/DensePhrases

Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering

https://github.com/kit-mrt/red-motion

Longformer: The Long-Document Transformer

https://github.com/kit-mrt/road-barlow-twins

Longformer: The Long-Document Transformer

https://github.com/lucashueda/long_sentence_transformer

Longformer: The Long-Document Transformer

https://github.com/mandarjoshi90/triviaqa

TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

https://github.com/microsoft/dialoglm

Longformer: The Long-Document Transformer

https://github.com/mim-solutions/bert_for_longer_texts

Longformer: The Long-Document Transformer

https://github.com/mim-solutions/roberta_for_longer_texts

Longformer: The Long-Document Transformer

https://github.com/mistralai/mistral-src

Longformer: The Long-Document Transformer

https://github.com/naver-ai/simseek

Longformer: The Long-Document Transformer

https://github.com/nidhikamal-emb/DPR_repo

Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering

https://github.com/openmatch/coco-dr

Text and Code Embeddings by Contrastive Pre-Training

https://github.com/princeton-nlp/DensePhrases

Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering

https://github.com/rvlopes/gloria

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

https://github.com/schenliu/longformer-chinese

Longformer: The Long-Document Transformer

https://github.com/shmsw25/GraphRetriever

Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering

https://github.com/solidsea98/neural-corpus-indexer-nci

A Neural Corpus Indexer for Document Retrieval

https://github.com/thakur-nandan/beir-colbert

Relevance-guided Supervision for OpenQA with ColBERT

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

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.