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Information Retrieval

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하위 태스크: 6
평가표: 33
보존된 평가 기록: 17

Information retrieval is the task of ranking a list of documents or search results in response to a query

<span style="color:grey; opacity: 0.6">( Image credit: sudhanshumittal )</span>

코드

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

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

공식 코드

Improving Passage Retrieval with Zero-Shot Question Generation

https://github.com/EdwinKim3069/XtarNet

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XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning

https://github.com/Eric-Wallace/trickme-interface

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Trick Me If You Can: Human-in-the-loop Generation of Adversarial Examples for Question Answering

https://github.com/EsmaeilNarimissa/RAG-Retrieval-Analysis

공식 코드

Exploring Information Retrieval Landscapes: An Investigation of a Novel Evaluation Techniques and Comparative Document Splitting Methods

https://github.com/FeiWang96/GTR

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Retrieving Complex Tables with Multi-Granular Graph Representation Learning

https://github.com/GIFRN/Rational-Probabilistic-Beliefs

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Exploring the Potential for Large Language Models to Demonstrate Rational Probabilistic Beliefs

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

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Expansion via Prediction of Importance with Contextualization

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

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Teaching a New Dog Old Tricks: Resurrecting Multilingual Retrieval Using Zero-shot Learning

https://github.com/Georgetown-IR-Lab/neuir-weak-supervision

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Content-Based Weak Supervision for Ad-Hoc Re-Ranking

https://github.com/Gompyn/re2com-opensource

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Retrieve and Refine: Exemplar-based Neural Comment Generation

https://github.com/Guzpenha/query_variation_generators

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Evaluating the Robustness of Retrieval Pipelines with Query Variation Generators

https://github.com/Guzpenha/transformer_rankers

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

https://github.com/Guzpenha/transformers_cl

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Curriculum Learning Strategies for IR: An Empirical Study on Conversation Response Ranking

https://github.com/HHansi/Embed2Detect

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Embed2Detect: Temporally Clustered Embedded Words for Event Detection in Social Media

https://github.com/HKUNLP/instructor-embedding

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One Embedder, Any Task: Instruction-Finetuned Text Embeddings

https://github.com/HLTCHKUST/CAiRE-COVID

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CAiRE-COVID: A Question Answering and Query-focused Multi-Document Summarization System for COVID-19 Scholarly Information Management

https://github.com/HarrieO/BalancingSpeedQualityOLTR

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Balancing Speed and Quality in Online Learning to Rank for Information Retrieval

https://github.com/Hayeonbang/PIAST

공식 코드

PIAST: A Multimodal Piano Dataset with Audio, Symbolic and Text

https://github.com/Hellisotherpeople/DebateSum

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DebateSum: A large-scale argument mining and summarization dataset

https://github.com/Hellisotherpeople/debate2vec

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DebateSum: A large-scale argument mining and summarization dataset

https://github.com/IBM/science-result-extractor

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Identification of Tasks, Datasets, Evaluation Metrics, and Numeric Scores for Scientific Leaderboards Construction

https://github.com/IBM/twitter-customer-care-document-prediction

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Conversational Document Prediction to Assist Customer Care Agents

https://github.com/Infini-AI-Lab/gsm_infinite

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GSM-Infinite: How Do Your LLMs Behave over Infinitely Increasing Context Length and Reasoning Complexity?

https://github.com/Irene323/GFTE

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GFTE: Graph-based Financial Table Extraction

https://github.com/J-zin/SNUH

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Integrating Semantics and Neighborhood Information with Graph-Driven Generative Models for Document Retrieval

https://github.com/Jeffyrao/TREC-Microblog-Datasets

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Multi-Perspective Relevance Matching with Hierarchical ConvNets for Social Media Search

https://github.com/JiapengL/multi_ling_search

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Cross-Lingual Document Retrieval with Smooth Learning

https://github.com/JiapengWu/Time-Aware-Incremental-Embedding

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TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion

https://github.com/Jinjiarui/DRSR

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A Deep Recurrent Survival Model for Unbiased Ranking

https://github.com/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/1.4.Biomedical_NER_SparkNLP_paper_reproduce.ipynb

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Biomedical Named Entity Recognition at Scale

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

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

https://github.com/Kim-Minseon/APGP

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Automatic Jailbreaking of the Text-to-Image Generative AI Systems

https://github.com/KoksiHub/Methods-For-SHREC-2021-Protein-Retrieval-and-Classification-Datasets

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SHREC 2021: Retrieval and classification of protein surfaces equipped with physical and chemical properties

https://github.com/Littleor/Personalized-DMER

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Personalized Dynamic Music Emotion Recognition with Dual-Scale Attention-Based Meta-Learning

https://github.com/LiuChang97/CLMN

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Cross-Lingual Low-Resource Set-to-Description Retrieval for Global E-Commerce

https://github.com/Lsyhprum/WEAVESS

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A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Search

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