Natural Questions
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yxf203/poisonarena
공식 코드PoisonArena: Uncovering Competing Poisoning Attacks in Retrieval-Augmented Generation
https://github.com/zhiyuanpeng/eloq
공식 코드ELOQ: Resources for Enhancing LLM Detection of Out-of-Scope Questions
https://github.com/zixuanke/lifelongsentclass
공식 코드Continual Learning with Knowledge Transfer for Sentiment Classification
https://github.com/zixuanke/pycontinual
공식 코드Continual Learning with Knowledge Transfer for Sentiment Classification
https://github.com/zorazrw/nqt-retrieval
공식 코드Table Retrieval May Not Necessitate Table-specific Model Design
https://github.com/DevSinghSachan/unsupervised-passage-reranking
End-to-End Training of Neural Retrievers for Open-Domain Question Answering
https://github.com/FenQQQ/Fusion-in-decoder
Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering
https://github.com/Heidelberg-NLP/discourse-aware-semantic-self-attention
Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering
https://github.com/IBM/ColBERT-practical
https://github.com/JunnYu/x-transformers-paddle
https://github.com/MindSpore-scientific/code-7/tree/main/DPT
https://github.com/ZIZUN/MAFiD
Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering
https://github.com/aivolcano/BERT_MRC_CLS
https://github.com/allenai/dolma
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
https://github.com/amzn/refuel-open-domain-qa
Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering
https://github.com/awslabs/diagnostic-robustness-text-to-sql
Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness
https://github.com/badripatro/MDN-VQG
Multimodal Differential Network for Visual Question Generation
https://github.com/bramiozo/PubScience
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
https://github.com/chingyaoc/vqg-tensorflow
https://github.com/cloneofsimo/RealFormer-pytorch
https://github.com/czy1999/MultiTQ
https://github.com/czy1999/SubGTR
https://github.com/d3mlab/cr-lt-kgqa
https://github.com/dreamstorm25/Generating-Natural-Questions-from-an-Image
https://github.com/facebookresearch/DPR
Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering
https://github.com/facebookresearch/FiD
Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering
https://github.com/facebookresearch/reconsider
RECONSIDER: Re-Ranking using Span-Focused Cross-Attention for Open Domain Question Answering
https://github.com/gooofy/zbrain
https://github.com/hltcoe/colbert-x
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/jaketae/realformer
https://github.com/jhyuklee/DensePhrases
Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering
https://github.com/justinaL/tag
CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.