Papers with Code 아카이브

Information Retrieval

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전체 기법 전체 데이터셋

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/cwitkowitz/lhvqt

Learning Sparse Analytic Filters for Piano Transcription

https://github.com/dddzeng/CMR_audiovisual

Deep Triplet Neural Networks with Cluster-CCA for Audio-Visual Cross-modal Retrieval

https://github.com/deepmind/narrativeqa

The NarrativeQA Reading Comprehension Challenge

https://github.com/deepset-ai/haystack

Dense Passage Retrieval for Open-Domain Question Answering

https://github.com/dglai/wsdm2022-challenge

Modeling Relational Data with Graph Convolutional Networks

https://github.com/dladustn95/ENMODEL

TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents

https://github.com/dladustn95/dialogGenerator_transformer

TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents

https://github.com/dladustn95/enLanguageModel

TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents

https://github.com/dlsun/ds-seminar

Deep Learning based Recommender System: A Survey and New Perspectives

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

Contextualized Sparse Representations for Real-Time Open-Domain Question Answering

https://github.com/dmlc/dgl/tree/master/examples/mxnet/rgcn

Modeling Relational Data with Graph Convolutional Networks

https://github.com/dmlc/dgl/tree/master/examples/pytorch/rgcn-hetero

Modeling Relational Data with Graph Convolutional Networks

https://github.com/dmlc/dgl/tree/master/examples/tensorflow/rgcn

Modeling Relational Data with Graph Convolutional Networks

https://github.com/donggyukimc/nash

NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing

https://github.com/dreji18/fairness-in-ai

An Approach to Ensure Fairness in News Articles

https://github.com/dujiaxin/semanticRetrievalMRS

Revealing the Importance of Semantic Retrieval for Machine Reading at Scale

https://github.com/effectiff-tech/homogeneity-scripts

ATR4S: Toolkit with State-of-the-art Automatic Terms Recognition Methods in Scala

https://github.com/efficientqa/retrieval-based-baselines

Dense Passage Retrieval for Open-Domain Question Answering

https://github.com/eladhoffer/TripletNet

Deep metric learning using Triplet network

https://github.com/emory-irlab/pyterrier_genrank

RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models

https://github.com/expertailab/spaceqa

ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT

https://github.com/exploration-lab/iitk-semeval-2024-task-1

TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learning

https://github.com/facebookresearch/Horizon

Seq2Slate: Re-ranking and Slate Optimization with RNNs

https://github.com/facebookresearch/ReAgent

Seq2Slate: Re-ranking and Slate Optimization with RNNs

https://github.com/facebookresearch/generative-recommenders

Revisiting Neural Retrieval on Accelerators

https://github.com/fangrouli/Document-embedding-generation-models

PatentMatch: A Dataset for Matching Patent Claims & Prior Art

https://github.com/florin-git/Base-vs-Instruct-LLMs-in-RAG-Systems

The Power of Noise: Redefining Retrieval for RAG Systems

https://github.com/garygsw/Nav-NNDial

Key-Value Retrieval Networks for Task-Oriented Dialogue

https://github.com/gdevos010/Scalable-Softmax

Scalable-Softmax Is Superior for Attention

https://github.com/gengchenmai/se-kge

SE-KGE: A Location-Aware Knowledge Graph Embedding Model for Geographic Question Answering and Spatial Semantic Lifting

https://github.com/gesina/bg_randomized_loce

Local Concept Embeddings for Analysis of Concept Distributions in Vision DNN Feature Spaces

https://github.com/giuseppefutia/semi

Modeling Relational Data with Graph Convolutional Networks

https://github.com/glb400/Toy-RecLM

Revisiting Neural Retrieval on Accelerators

https://github.com/glee4810/EHRSQL

Overview of the EHRSQL 2024 Shared Task on Reliable Text-to-SQL Modeling on Electronic Health Records

https://github.com/google-deepmind/narrativeqa

The NarrativeQA Reading Comprehension Challenge

https://github.com/google-research/chirp

BIRB: A Generalization Benchmark for Information Retrieval in Bioacoustics

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