Papers with Code 아카이브

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/manveertamber/content_injection_attacks

공식 코드

Illusions of Relevance: Using Content Injection Attacks to Deceive Retrievers, Rerankers, and LLM Judges

https://github.com/mariaheuss/rankingshap

공식 코드

RankingSHAP -- Listwise Feature Attribution Explanations for Ranking Models

https://github.com/marl/crepe

공식 코드

CREPE: A Convolutional Representation for Pitch Estimation

https://github.com/martiansideofthemoon/relic-retrieval

공식 코드

RELIC: Retrieving Evidence for Literary Claims

https://github.com/mathetake/intergo

공식 코드

Greedy Optimized Multileaving for Personalization

https://github.com/mattbierbaum/arxiv-public-datasets

공식 코드

On the Use of ArXiv as a Dataset

https://github.com/mdenizturkmen/ecir2023

공식 코드

New Metrics to Encourage Innovation and Diversity in Information Retrieval Approaches

https://github.com/mdmustafizurrahman/An-Information-Retrieval-Approach-to-Building-Datasets-for-Hate-Speech-Detection

공식 코드

An Information Retrieval Approach to Building Datasets for Hate Speech Detection

https://github.com/medicinetoken/medical-graph-rag

공식 코드

Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented Generation

https://github.com/medtray/StruBERT

공식 코드

StruBERT: Structure-aware BERT for Table Search and Matching

https://github.com/meetelise/surprise-similarity

공식 코드

Taken by Surprise: Contrast effect for Similarity Scores

https://github.com/mega002/DocQN

공식 코드

Learning to Search in Long Documents Using Document Structure

https://github.com/megagonlabs/sato

공식 코드

Sato: Contextual Semantic Type Detection in Tables

https://github.com/megamine25/Music-genre-classification

공식 코드

Music Genre Classification using Large Language Models

https://github.com/mehdi-mbl/WordCoding

공식 코드

Combining a Context Aware Neural Network with a Denoising Autoencoder for Measuring String Similarities

https://github.com/mengshor/JTAV

공식 코드

JTAV: Jointly Learning Social Media Content Representation by Fusing Textual, Acoustic, and Visual Features

https://github.com/menouarazib/eventdetector

공식 코드

A Comprehensive Python Library for Deep Learning-Based Event Detection in Multivariate Time Series Data and Information Retrieval in NLP

https://github.com/menouarazib/informationretrievalinnlp

공식 코드

A Comprehensive Python Library for Deep Learning-Based Event Detection in Multivariate Time Series Data and Information Retrieval in NLP

https://github.com/meow-e/usimagent

공식 코드

USimAgent: Large Language Models for Simulating Search Users

https://github.com/mequanent/ChantingModeClassification

공식 코드

Computational Analysis of Yaredawi YeZema Silt in Ethiopian Orthodox Tewahedo Church Chants

https://github.com/mesnico/TERAN

공식 코드

Fine-grained Visual Textual Alignment for Cross-Modal Retrieval using Transformer Encoders

https://github.com/mesnico/TERN

공식 코드

Transformer Reasoning Network for Image-Text Matching and Retrieval

https://github.com/metemaad/TrajLib

공식 코드

On feature selection and evaluation of transportation mode prediction strategies

https://github.com/michaelwilliamtang/referral-augment

공식 코드

Referral Augmentation for Zero-Shot Information Retrieval

https://github.com/microsoft/ANCE

공식 코드

Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

https://github.com/microsoft/FILM

공식 코드

Make Your LLM Fully Utilize the Context

https://github.com/microsoft/comphrdoc

공식 코드

Detect-Order-Construct: A Tree Construction based Approach for Hierarchical Document Structure Analysis

https://github.com/microsoft/eureka-ml-insights

공식 코드

Eureka: Evaluating and Understanding Large Foundation Models

https://github.com/microsoft/lmops

공식 코드

MiniLLM: Knowledge Distillation of Large Language Models

https://github.com/microsoft/macaw

공식 코드

Macaw: An Extensible Conversational Information Seeking Platform

https://github.com/microsoft/ms-marco-web-search

공식 코드

MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels

https://github.com/microsoft/muzic

공식 코드

CLaMP: Contrastive Language-Music Pre-training for Cross-Modal Symbolic Music Information Retrieval

https://github.com/microsoft/muzic/tree/main/clamp

공식 코드

CLaMP: Contrastive Language-Music Pre-training for Cross-Modal Symbolic Music Information Retrieval

https://github.com/microsoft/simxns

공식 코드

MASTER: Multi-task Pre-trained Bottlenecked Masked Autoencoders are Better Dense Retrievers

https://github.com/microsoft/unilm

공식 코드

SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval

https://github.com/microsoft/unilm/blob/master/Diff-Transformer/

공식 코드

Differential Transformer

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