Papers with Code 아카이브
Retrieval
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A methodology that involves selecting relevant data or examples from a large dataset to support tasks like prediction, learning, or inference. It enhances models by providing context or additional information, often used in systems like retrieval-augmented generation or in-context learning.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/chenshunpeng/FoL
공식 코드Focus on Local: Finding Reliable Discriminative Regions for Visual Place Recognition
https://github.com/chentong0/factoid-wiki
공식 코드Dense X Retrieval: What Retrieval Granularity Should We Use?
https://github.com/chenxiaofei-cs/kobo
공식 코드Knowledge Boosting: Rethinking Medical Contrastive Vision-Language Pre-Training
https://github.com/chenyiqun/mmoa-rag
공식 코드Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement Learning
https://github.com/chenzhongwu20/rulerag_icl_ft
공식 코드RuleRAG: Rule-guided retrieval-augmented generation with language models for question answering
https://github.com/chiang-yuan/llamp
공식 코드https://github.com/chiangsonw/cala
공식 코드CaLa: Complementary Association Learning for Augmenting Composed Image Retrieval
https://github.com/chihhuiho/VISPE
공식 코드Exploit Clues from Views: Self-Supervised and Regularized Learning for Multiview Object Recognition
https://github.com/chilab1/unipagpt-23
공식 코드Unipa-GPT: Large Language Models for university-oriented QA in Italian
https://github.com/chingyaoc/infoot
공식 코드https://github.com/chinmayad/motiondescriptions
공식 코드Diving Deep into the Motion Representation of Video-Text Models
https://github.com/chorowski-lab/zs2021
공식 코드Information Retrieval for ZeroSpeech 2021: The Submission by University of Wroclaw
https://github.com/chridey/fever2-columbia
공식 코드DeSePtion: Dual Sequence Prediction and Adversarial Examples for Improved Fact-Checking
https://github.com/chris210634/metric-learning-using-contextual-similarity
공식 코드Supervised Metric Learning to Rank for Retrieval via Contextual Similarity Optimization
https://github.com/chris210634/mudg
공식 코드Multimodal Unsupervised Domain Generalization by Retrieving Across the Modality Gap
https://github.com/chrisdonahue/sheetsage
공식 코드https://github.com/chrismun/vvllm
공식 코드LLM4VV: Developing LLM-Driven Testsuite for Compiler Validation
https://github.com/chrispla/mir_ref
공식 코드mir_ref: A Representation Evaluation Framework for Music Information Retrieval Tasks
https://github.com/christofhenkel/kaggle-landmark-2021-1st-place
공식 코드Efficient large-scale image retrieval with deep feature orthogonality and Hybrid-Swin-Transformers
https://github.com/chrschy/fact-finder
공식 코드Fact Finder -- Enhancing Domain Expertise of Large Language Models by Incorporating Knowledge Graphs
https://github.com/chuanmeng/qpp-genre
공식 코드Query Performance Prediction using Relevance Judgments Generated by Large Language Models
https://github.com/chuanmeng/qpp4cs
공식 코드Query Performance Prediction: From Ad-hoc to Conversational Search
https://github.com/chuanmeng/rlt4reranking
공식 코드Ranked List Truncation for Large Language Model-based Re-Ranking
https://github.com/chuhac/atm-rag
공식 코드ATM: Adversarial Tuning Multi-agent System Makes a Robust Retrieval-Augmented Generator
https://github.com/chuhanxx/helping_hand_for_egocentric_videos
공식 코드Helping Hands: An Object-Aware Ego-Centric Video Recognition Model
https://github.com/chunmeifeng/sprc
공식 코드https://github.com/chunmeifeng/vqa4cir
공식 코드VQA4CIR: Boosting Composed Image Retrieval with Visual Question Answering
https://github.com/chymaera96/neuralsampleid
공식 코드Refining music sample identification with a self-supervised graph neural network
https://github.com/ciodar/cultural-heritage-diffaug
공식 코드Diffusion Based Augmentation for Captioning and Retrieval in Cultural Heritage
https://github.com/cisnlp/colexificationnet
공식 코드https://github.com/cisnlp/xampler
공식 코드XAMPLER: Learning to Retrieve Cross-Lingual In-Context Examples
https://github.com/ckdjrkffz/multi-stage-reranking
공식 코드https://github.com/claclark/cottontail
공식 코드https://github.com/claclark/preferences
공식 코드https://github.com/claudiashu/una
공식 코드Unsupervised hard Negative Augmentation for contrastive learning
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