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/irgroup/clef2021-web-prf
공식 코드Evaluating Elements of Web-based Data Enrichment for Pseudo-Relevance Feedback Retrieval
https://github.com/irgroup/ecir2022-uqv-sim
공식 코드https://github.com/irgroup/lwda2023-ir-community
공식 코드https://github.com/irgroup/repro_eval
공식 코드repro_eval: A Python Interface to Reproducibility Measures of System-oriented IR Experiments
https://github.com/irgroup/simiir-wtr
공식 코드https://github.com/irgroup/suir
공식 코드Context-Driven Interactive Query Simulations Based on Generative Large Language Models
https://github.com/irgroup/validating-synthetic-usage-data
공식 코드https://github.com/irislucent/motif-encoder
공식 코드https://github.com/irlabamsterdam/cone-rag
공식 코드Conversational Gold: Evaluating Personalized Conversational Search System using Gold Nuggets
https://github.com/irvingmeng/securevector
공식 코드Towards Privacy-Preserving, Real-Time and Lossless Feature Matching
https://github.com/is2ai/kazqad
공식 코드https://github.com/isaacwasserman/LongRAG
공식 코드Enhancing Retrieval in QA Systems with Derived Feature Association
https://github.com/ischlag/fast-weight-transformers
공식 코드https://github.com/isekulic/longformer-marco
공식 코드https://github.com/isekulic/mimics-EL-benchmark
공식 코드https://github.com/iseratho/framefinder
공식 코드FrameFinder: Explorative Multi-Perspective Framing Extraction from News Headlines
https://github.com/ishalyminov/babi_tools
공식 코드Challenging Neural Dialogue Models with Natural Data: Memory Networks Fail on Incremental Phenomena
https://github.com/isi-nlp/recap
공식 코드RECAP: Retrieval-Enhanced Context-Aware Prefix Encoder for Personalized Dialogue Response Generation
https://github.com/isl-cv/chitransformer
공식 코드https://github.com/islab-github/cdatasets
공식 코드Semantic-Preserving Augmentation for Robust Image-Text Retrieval
https://github.com/ispamm/GRAM
공식 코드https://github.com/ispras/atr4s
공식 코드ATR4S: Toolkit with State-of-the-art Automatic Terms Recognition Methods in Scala
https://github.com/ita9naiwa/rlrd-aaai2022
공식 코드An Efficient Combinatorial Optimization Model Using Learning-to-Rank Distillation
https://github.com/itaymanes/k-qa
공식 코드https://github.com/ivanaer/g-universal-clip
공식 코드General Image Descriptors for Open World Image Retrieval using ViT CLIP
https://github.com/izhx/uni-rep
공식 코드https://github.com/j-min/HiREST
공식 코드https://github.com/j-min/clip-caption-reward
공식 코드https://github.com/j-min/dalleval
공식 코드DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generation Models
https://github.com/j-rossi-nl/verbcl
공식 코드VerbCL: A Dataset of Verbatim Quotes for Highlight Extraction in Case Law
https://github.com/j991222/mirb
공식 코드https://github.com/jCarrilloDeAlbornoz/RBU
공식 코드An Axiomatic Analysis of Diversity Evaluation Metrics: Introducing the Rank-Biased Utility Metric
https://github.com/jac99/minkloc3dv2
공식 코드Improving Point Cloud Based Place Recognition with Ranking-based Loss and Large Batch Training
https://github.com/jacklxc/cts4citationtextgeneration
공식 코드https://github.com/jackryo/ricap
공식 코드Data Augmentation using Random Image Cropping and Patching for Deep CNNs
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.