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Passage Retrieval

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평가표: 19
보존된 평가 기록: 38

Passage retrieval is a specialized type of IR application that retrieves relevant passages (or pieces of text) rather than an entire ranked set of documents.

코드

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

https://github.com/AdeDZY/DeepCT

공식 코드

Context-Aware Sentence/Passage Term Importance Estimation For First Stage Retrieval

https://github.com/AhmedHussKhalifa/Dense_Passage_Retrieval_in_Conversational_Search

공식 코드

Dense Passage Retrieval in Conversational Search

https://github.com/AkariAsai/CORA

공식 코드

One Question Answering Model for Many Languages with Cross-lingual Dense Passage Retrieval

https://github.com/Ariya12138/CORAL

공식 코드

CORAL: Benchmarking Multi-turn Conversational Retrieval-Augmentation Generation

https://github.com/CPJKU/DeepGenIR

공식 코드

A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models

https://github.com/CPJKU/information_retrieval_fairness_debiasing

공식 코드

Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation for BERT Rankers

https://github.com/DevSinghSachan/unsupervised-passage-reranking

공식 코드

Improving Passage Retrieval with Zero-Shot Question Generation

https://github.com/Georgetown-IR-Lab/epic-neural-ir

공식 코드

Expansion via Prediction of Importance with Contextualization

https://github.com/Guzpenha/transformer_rankers

공식 코드

Do the Findings of Document and Passage Retrieval Generalize to the Retrieval of Responses for Dialogues?

https://github.com/KNOT-FIT-BUT/R2-D2

공식 코드

R2-D2: A Modular Baseline for Open-Domain Question Answering

https://github.com/McGill-NLP/MLQuestions

공식 코드

Back-Training excels Self-Training at Unsupervised Domain Adaptation of Question Generation and Passage Retrieval

https://github.com/UKPLab/arxiv2024-missciplus

공식 코드

Grounding Fallacies Misrepresenting Scientific Publications in Evidence

https://github.com/UKPLab/beir

공식 코드

BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models

https://github.com/alibaba-nlp/multi-cpr

공식 코드

Multi-CPR: A Multi Domain Chinese Dataset for Passage Retrieval

https://github.com/alirezasalemi7/pretraining-multimodal-dense-retriever-for-okvqa

공식 코드

Pre-Training Multi-Modal Dense Retrievers for Outside-Knowledge Visual Question Answering

https://github.com/aloneirew/coresearch

공식 코드

Cross-document Event Coreference Search: Task, Dataset and Modeling

https://github.com/anmoln94/Team_LLM2KB_LM-KBC-2023

공식 코드

LLM2KB: Constructing Knowledge Bases using instruction tuned context aware Large Language Models

https://github.com/apple/ml-qrecc

공식 코드

Open-Domain Question Answering Goes Conversational via Question Rewriting

https://github.com/arvinzhuang/dsi-qg

공식 코드

Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation

https://github.com/asash/recjpq

공식 코드

RecJPQ: Training Large-Catalogue Sequential Recommenders

https://github.com/awslabs/neural-retrieval

공식 코드

Embedding-based Zero-shot Retrieval through Query Generation

https://github.com/baidu/DuReader

공식 코드

DuReader_retrieval: A Large-scale Chinese Benchmark for Passage Retrieval from Web Search Engine

https://github.com/caskcsg/CoT-MAE

공식 코드

ConTextual Masked Auto-Encoder for Dense Passage Retrieval

https://github.com/caskcsg/ir

공식 코드

ConTextual Masked Auto-Encoder for Dense Passage Retrieval

https://github.com/castorini/dhr

공식 코드

Aggretriever: A Simple Approach to Aggregate Textual Representations for Robust Dense Passage Retrieval

https://github.com/chuanmeng/qpp4cs

공식 코드

Query Performance Prediction: From Ad-hoc to Conversational Search

https://github.com/clips/mfaq

공식 코드

MFAQ: a Multilingual FAQ Dataset

https://github.com/daehuikim/gure

공식 코드

GuRE:Generative Query REwriter for Legal Passage Retrieval

https://github.com/datascienceuibk/arabicaqa

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ArabicaQA: A Comprehensive Dataset for Arabic Question Answering

https://github.com/davidmrau/transformer-vs-bm25

공식 코드

How Different are Pre-trained Transformers for Text Ranking?

https://github.com/declare-lab/exemplary-empathy

공식 코드

Exemplars-guided Empathetic Response Generation Controlled by the Elements of Human Communication

https://github.com/dennlinger/TopicalChange

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Structural Text Segmentation of Legal Documents

https://github.com/deriq-qian-dong/iii-retriever

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I^3 Retriever: Incorporating Implicit Interaction in Pre-trained Language Models for Passage Retrieval

https://github.com/diazf/indri

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Duet at TREC 2019 Deep Learning Track

https://github.com/dmis-lab/tour

공식 코드

Optimizing Test-Time Query Representations for Dense Retrieval

https://github.com/elviswxy/Gen-IR_PSPT

공식 코드

Passage-specific Prompt Tuning for Passage Reranking in Question Answering with Large Language Models

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