https://github.com/teakinboyewa/autonomousgis_geodataretrieveragent
공식 코드An Autonomous GIS Agent Framework for Geospatial Data Retrieval
Papers with Code 아카이브
Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
- 19
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/teamnlp/typed-rag
공식 코드Typed-RAG: Type-aware Multi-Aspect Decomposition for Non-Factoid Question Answering
https://github.com/tech-srl/code2seq
공식 코드code2seq: Generating Sequences from Structured Representations of Code
https://github.com/technicolor-research/dsve-loc
공식 코드Finding beans in burgers: Deep semantic-visual embedding with localization
https://github.com/technicolor-research/faiss-quickeradc
공식 코드Quicker ADC : Unlocking the hidden potential of Product Quantization with SIMD
https://github.com/technicolor-research/quick-adc
공식 코드https://github.com/technion-cs-nlp/re-gen-ir
공식 코드https://github.com/technomad-ds/lovr-benchmark
공식 코드LoVR: A Benchmark for Long Video Retrieval in Multimodal Contexts
https://github.com/teddy-xionggz/medrag
공식 코드https://github.com/teddy-xionggz/mirage
공식 코드https://github.com/tedunderwood/genredistance
공식 코드https://github.com/temphero/heronet
공식 코드HeroNet: A Hybrid Retrieval-Generation Network for Conversational Bots
https://github.com/tencentarc/mcq
공식 코드Bridging Video-text Retrieval with Multiple Choice Questions
https://github.com/tencentarc/umt
공식 코드UMT: Unified Multi-modal Transformers for Joint Video Moment Retrieval and Highlight Detection
https://github.com/tencentyouturesearch/personretrieval-ivt
공식 코드See Finer, See More: Implicit Modality Alignment for Text-based Person Retrieval
https://github.com/tenghaohuang/pluto
공식 코드Planning and Editing What You Retrieve for Enhanced Tool Learning
https://github.com/tensorflow/models
공식 코드Large-Scale Image Retrieval with Attentive Deep Local Features
https://github.com/tensorflow/tensorflow
공식 코드TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
https://github.com/terarachang/dataicl
공식 코드https://github.com/terrier-org/pyterrier
공식 코드Declarative Experimentation in Information Retrieval using PyTerrier
https://github.com/terrierteam/ir_measures
공식 코드https://github.com/terrierteam/pyterrier_adaptive
공식 코드https://github.com/terrierteam/pyterrier_colbert
공식 코드Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval
https://github.com/terrierteam/pyterrier_doc2query
공식 코드https://github.com/terrierteam/pyterrier_rag
공식 코드Constructing and Evaluating Declarative RAG Pipelines in PyTerrier
https://github.com/terrypei/nnretrieval
공식 코드https://github.com/text-machine-lab/xword_benchmark
공식 코드Down and Across: Introducing Crossword-Solving as a New NLP Benchmark
https://github.com/texttron/hyde
공식 코드https://github.com/texttron/tevatron
공식 코드Tevatron: An Efficient and Flexible Toolkit for Dense Retrieval
https://github.com/tfburns/cdam
공식 코드Semantically-correlated memories in a dense associative model
https://github.com/tgeral68/continual_learning_of_long_topic
공식 코드Continual Learning of Long Topic Sequences in Neural Information Retrieval
https://github.com/thaihungle/sm
공식 코드Beyond Surprise: Improving Exploration Through Surprise Novelty
https://github.com/thakur-nandan/income
공식 코드https://github.com/thakur-nandan/sprint
공식 코드SPRINT: A Unified Toolkit for Evaluating and Demystifying Zero-shot Neural Sparse Retrieval
https://github.com/thammegowda/007-mt-eval-macro
공식 코드https://github.com/the-bird-F/GLM-Voice-RAG
공식 코드Enhancing Speech-to-Speech Dialogue Modeling with End-to-End Retrieval-Augmented Generation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.