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/shaoxiongji/awesome-knowledge-graph

Knowledge Representation Learning: A Quantitative Review

https://github.com/shenweichen/DeepCTR

Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data

https://github.com/shenweichen/DeepCTR-PyTorch

Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data

https://github.com/shenweichen/deepmatch

Multi-Interest Network with Dynamic Routing for Recommendation at Tmall

https://github.com/shibing624/text2vec

One Embedder, Any Task: Instruction-Finetuned Text Embeddings

https://github.com/shijx12/kqapro_baselines

Modeling Relational Data with Graph Convolutional Networks

https://github.com/sjj0403/GSCS

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

https://github.com/soco-ai/SF-QA

VisualSparta: An Embarrassingly Simple Approach to Large-scale Text-to-Image Search with Weighted Bag-of-words

https://github.com/soldni/pyterrier_sentence_transformers

Unsupervised Dense Information Retrieval with Contrastive Learning

https://github.com/songyang0716/Topic_Modeling

Probabilistic Latent Semantic Analysis

https://github.com/sophia1488/symbolic-melody-identification

A Convolutional Approach to Melody Line Identification in Symbolic Scores

https://github.com/srgrace/contextual-compression

Extending Context Window of Large Language Models via Semantic Compression

https://github.com/stanford-futuredata/Baleen

ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction

https://github.com/stormieGal/mediLearn

A Question-Entailment Approach to Question Answering

https://github.com/sung-yeon-kim/GENIUS-CVPR25

GENIUS: A Generative Framework for Universal Multimodal Search

https://github.com/sunhwan-lee/recommender_system

Deep Learning based Recommender System: A Survey and New Perspectives

https://github.com/susurrant/flow-imputation

Modeling Relational Data with Graph Convolutional Networks

https://github.com/susurrant/spatial-interaction-modeling

Modeling Relational Data with Graph Convolutional Networks

https://github.com/tanyakoh/CBIR

Content-based image retrieval tutorial

https://github.com/terrierteam/pyterrier_ance

Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

https://github.com/terrierteam/pyterrier_deepct

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

https://github.com/terrierteam/pyterrier_doc2query

Declarative Experimentation in Information Retrieval using PyTerrier

https://github.com/terrierteam/pyterrier_dr

Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

https://github.com/terrierteam/pyterrier_t5

Declarative Experimentation in Information Retrieval using PyTerrier

https://github.com/texttron/tevatron

Dense Passage Retrieval for Open-Domain Question Answering

https://github.com/texttron/tevatron/tree/main/examples/repllama

Fine-Tuning LLaMA for Multi-Stage Text Retrieval

https://github.com/textvec/textvec

Inverse-Category-Frequency based supervised term weighting scheme for text categorization

https://github.com/thakur-nandan/beir-colbert

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

https://github.com/the-pythoncoder/councelChatbot2

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

https://github.com/the-pythoncoder/counsel-chat

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

https://github.com/thirdairesearch/bolt_benchmarks

BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU Hardware

https://github.com/thiviyanT/torch-rgcn

Modeling Relational Data with Graph Convolutional Networks

https://github.com/thu-coai/CDial-GPT

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

https://github.com/thunlp/clueanchor

Atlas: Few-shot Learning with Retrieval Augmented Language Models

https://github.com/tkipf/gae

Modeling Relational Data with Graph Convolutional Networks

https://github.com/toooooodo/rgcn-linkprediction

Modeling Relational Data with Graph Convolutional Networks

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