https://github.com/8421bcd/demorank
공식 코드DemoRank: Selecting Effective Demonstrations for Large Language Models in Ranking Task
Papers with Code 아카이브
Passage Ranking
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/8421bcd/fullrank
공식 코드Sliding Windows Are Not the End: Exploring Full Ranking with Long-Context Large Language Models
https://github.com/Alibaba-NLP/HLATR
공식 코드HLATR: Enhance Multi-stage Text Retrieval with Hybrid List Aware Transformer Reranking
https://github.com/Georgetown-IR-Lab/epic-neural-ir
공식 코드Expansion via Prediction of Importance with Contextualization
https://github.com/asash/shallow-cross-encoders
공식 코드https://github.com/cmacdonald/pyterrier_colbert
공식 코드Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval
https://github.com/embeddings-benchmark/mteb/blob/main/mteb/tasks/Retrieval/multilingual/CUREv1Retrieval.py
공식 코드CURE: A dataset for Clinical Understanding & Retrieval Evaluation
https://github.com/gsidiropoulos/dense-retrieval-against-misspellings
공식 코드Analysing the Robustness of Dual Encoders for Dense Retrieval Against Misspellings
https://github.com/gsidiropoulos/passage_retrieval_for_spoken_qa
공식 코드On the Impact of Speech Recognition Errors in Passage Retrieval for Spoken Question Answering
https://github.com/ielab/typos-aware-bert
공식 코드Dealing with Typos for BERT-based Passage Retrieval and Ranking
https://github.com/jingtaozhan/RepBERT-Index
공식 코드RepBERT: Contextualized Text Embeddings for First-Stage Retrieval
https://github.com/laujames/pat
공식 코드Order-Disorder: Imitation Adversarial Attacks for Black-box Neural Ranking Models
https://github.com/liuqi6777/pe_rank
공식 코드Leveraging Passage Embeddings for Efficient Listwise Reranking with Large Language Models
https://github.com/liyongqi67/ltrgr
공식 코드https://github.com/magkai/CROWN
공식 코드CROWN: Conversational Passage Ranking by Reasoning over Word Networks
https://github.com/microsoft/simxns
공식 코드LEAD: Liberal Feature-based Distillation for Dense Retrieval
https://github.com/mrjleo/ranking-models
공식 코드Exploiting Sentence-Level Representations for Passage Ranking
https://github.com/openmatch/fit5
공식 코드Fusion-in-T5: Unifying Document Ranking Signals for Improved Information Retrieval
https://github.com/sebastian-hofstaetter/neural-ranking-kd
공식 코드Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation
https://github.com/sebastianarnold/cdv
공식 코드Learning Contextualized Document Representations for Healthcare Answer Retrieval
https://github.com/sunnweiwei/rankgpt
공식 코드Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents
https://github.com/svakulenk0/QRQA
공식 코드https://github.com/terrierteam/pyterrier_adaptive
공식 코드https://github.com/terrierteam/pyterrier_colbert
공식 코드Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval
https://github.com/thuir/t2ranking
공식 코드T2Ranking: A large-scale Chinese Benchmark for Passage Ranking
https://github.com/ulab-uiuc/iranker
공식 코드https://github.com/unicamp-dl/mMARCO
공식 코드mMARCO: A Multilingual Version of the MS MARCO Passage Ranking Dataset
https://github.com/webis-de/ictir-22
공식 코드https://github.com/Mandeep-Rathee/quam
https://github.com/Xiao0728/ColBERT-PRF-VirtualAppendix
Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval
https://github.com/castorini/pygaggle
Document Ranking with a Pretrained Sequence-to-Sequence Model
https://github.com/claclark/Compatibility
https://github.com/dfcf93/MSMARCO
https://github.com/ielab/characterbert-dr
Dealing with Typos for BERT-based Passage Retrieval and Ranking
https://github.com/jingtaozhan/JPQ
RepBERT: Contextualized Text Embeddings for First-Stage Retrieval
https://github.com/jingtaozhan/repconc
RepBERT: Contextualized Text Embeddings for First-Stage Retrieval
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.