https://github.com/wangpeisyuan/gcl-formula-retrieval
공식 코드The Effectiveness of Graph Contrastive Learning on Mathematical Information Retrieval
Papers with Code 아카이브
Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
- 11
- 보존된 평가 기록
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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/wangpinggl/TREQS
공식 코드Text-to-SQL Generation for Question Answering on Electronic Medical Records
https://github.com/wangskygit/passage-sieve
공식 코드https://github.com/wangt-cn/eqben
공식 코드Equivariant Similarity for Vision-Language Foundation Models
https://github.com/wangwenhao0716/v2l
공식 코드V$^2$L: Leveraging Vision and Vision-language Models into Large-scale Product Retrieval
https://github.com/wangxu-scu/CoDA
공식 코드Correspondence-Free Domain Alignment for Unsupervised Cross-Domain Image Retrieval
https://github.com/wangzhecheng/skyscript
공식 코드SkyScript: A Large and Semantically Diverse Vision-Language Dataset for Remote Sensing
https://github.com/wangzhichuan123/teda
공식 코드https://github.com/wanng-ide/ealm
공식 코드EALM: Introducing Multidimensional Ethical Alignment in Conversational Information Retrieval
https://github.com/waylonli/match
공식 코드BERT is not The Count: Learning to Match Mathematical Statements with Proofs
https://github.com/wayne-mai/egoloc
공식 코드EgoLoc: Revisiting 3D Object Localization from Egocentric Videos with Visual Queries
https://github.com/wbbeyourself/scm4llms
공식 코드Enhancing Large Language Model with Self-Controlled Memory Framework
https://github.com/wbrun0/LawngNLI
공식 코드https://github.com/wbs2788/vmb
공식 코드Multimodal Music Generation with Explicit Bridges and Retrieval Augmentation
https://github.com/wbsg-uni-mannheim/contrastive-product-matching
공식 코드https://github.com/wchen342/SketchyGAN
공식 코드SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesis
https://github.com/wdimmy/graphretrieval
공식 코드An Empirical Study of Retrieval-enhanced Graph Neural Networks
https://github.com/wdr123/darp-sbir
공식 코드Deep Reinforced Attention Regression for Partial Sketch Based Image Retrieval
https://github.com/weaidb/awesome-data-llm
공식 코드https://github.com/weaidb/awsome-data-llm
공식 코드https://github.com/webeng/llm_knowledge_gap_finder
공식 코드Harnessing Retrieval-Augmented Generation (RAG) for Uncovering Knowledge Gaps
https://github.com/webis-de/acl-22
공식 코드Clickbait Spoiling via Question Answering and Passage Retrieval
https://github.com/webis-de/archive-query-log
공식 코드https://github.com/webis-de/arxiv24-ranking-generated-answers
공식 코드https://github.com/webis-de/ecir-24
공식 코드Investigating the Effects of Sparse Attention on Cross-Encoders
https://github.com/webis-de/ecir25-counterfactual-query-rewriting
공식 코드Counterfactual Query Rewriting to Use Historical Relevance Feedback
https://github.com/webis-de/ictir-22
공식 코드https://github.com/webis-de/lightning-ir
공식 코드https://github.com/webis-de/scolia25-xsum
공식 코드Ask, Retrieve, Summarize: A Modular Pipeline for Scientific Literature Summarization
https://github.com/webis-de/sigir-23
공식 코드https://github.com/webis-de/spire-22
공식 코드https://github.com/webis-de/waka
공식 코드https://github.com/weitong8591/vop
공식 코드Breaking the Frame: Visual Place Recognition by Overlap Prediction
https://github.com/weiweisong415/Demo_AHCL_for_TGRS2022
공식 코드Asymmetric Hash Code Learning for Remote Sensing Image Retrieval
https://github.com/weizhepei/instructrag
공식 코드InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales
https://github.com/wellecks/naturalproofs
공식 코드NaturalProofs: Mathematical Theorem Proving in Natural Language
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.