https://github.com/fla-sil/PyTorrent
공식 코드AugmentedCode: Examining the Effects of Natural Language Resources in Code Retrieval Models
Papers with Code 아카이브
Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 3
- 평가표
- 11
- 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/flageval-baai/flagevalmm
공식 코드FlagEvalMM: A Flexible Framework for Comprehensive Multimodal Model Evaluation
https://github.com/flagopen/flagembedding
공식 코드https://github.com/flair-thu/creamfl
공식 코드Multimodal Federated Learning via Contrastive Representation Ensemble
https://github.com/flame-chasers/syntbpr
공식 코드An Empirical Study of Validating Synthetic Data for Text-Based Person Retrieval
https://github.com/flame-chasers/tbps-clip
공식 코드https://github.com/fletcherjiang/llmepet
공식 코드Prior Knowledge Integration via LLM Encoding and Pseudo Event Regulation for Video Moment Retrieval
https://github.com/flipkart-incubator/fk-visual-search
공식 코드Deep Learning based Large Scale Visual Recommendation and Search for E-Commerce
https://github.com/floatsdsds/sbg
공식 코드Modeling User Behavior with Graph Convolution for Personalized Product Search
https://github.com/florianlanger/sparc
공식 코드SPARC: Sparse Render-and-Compare for CAD model alignment in a single RGB image
https://github.com/florin-git/Base-vs-Instruct-LLMs-in-RAG-Systems
공식 코드A Tale of Trust and Accuracy: Base vs. Instruct LLMs in RAG Systems
https://github.com/florin-git/The-Power-of-Noise
공식 코드https://github.com/flyfree5/lahore
공식 코드Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval
https://github.com/fmthoker/skeleton-contrast
공식 코드https://github.com/fomorians/contextual_rnn
공식 코드https://github.com/foolwood/DRL
공식 코드Disentangled Representation Learning for Text-Video Retrieval
https://github.com/for-ai/goodtriever
공식 코드Goodtriever: Adaptive Toxicity Mitigation with Retrieval-augmented Models
https://github.com/ford666/raf21_tm_retrieval
공식 코드Nonconvex optimization for optimum retrieval of the transmission matrix of a multimode fiber
https://github.com/forrest-stone/diversity
공식 코드Result Diversification in Search and Recommendation: A Survey
https://github.com/fpgasystems/MLWeaving
공식 코드https://github.com/fpthink/EPC-Net
공식 코드Efficient 3D Point Cloud Feature Learning for Large-Scale Place Recognition
https://github.com/francesco-sovrano/automating-regulatory-compliance-an-empirical-study-on-ranking-transparency-of-eu-online-platforms
공식 코드https://github.com/francesco-sovrano/doxpy
공식 코드An Objective Metric for Explainable AI: How and Why to Estimate the Degree of Explainability
https://github.com/franco-galante/rgb-model
공식 코드Information Retrieval in the Age of Generative AI: The RGB Model
https://github.com/franfranz/emecomm_context
공식 코드Communication breakdown: On the low mutual intelligibility between human and neural captioning
https://github.com/frankxu2004/knnlm-why
공식 코드https://github.com/fraunhofer-iais/chunking-strategies
공식 코드Rethinking Chunk Size For Long-Document Retrieval: A Multi-Dataset Analysis
https://github.com/fredfung007/cityflow-nl
공식 코드CityFlow-NL: Tracking and Retrieval of Vehicles at City Scale by Natural Language Descriptions
https://github.com/freedomintelligence/huatuo-26m
공식 코드https://github.com/freedomintelligence/rag-instruct
공식 코드RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented Instructions
https://github.com/freedomintelligence/remop
공식 코드https://github.com/frenzymath/REAL-Prover
공식 코드REAL-Prover: Retrieval Augmented Lean Prover for Mathematical Reasoning
https://github.com/freshman97/csu
공식 코드https://github.com/friedrichor/UNITE
공식 코드Modality Curation: Building Universal Embeddings for Advanced Multimodal Information Retrieval
https://github.com/frischwood/hemu-dev
공식 코드Retrieval of Surface Solar Radiation through Implicit Albedo Recovery from Temporal Context
https://github.com/fromm-m/ecir2021-am-search
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.