https://github.com/xiaowu0162/sync-ralm-faithfulness
공식 코드Synchronous Faithfulness Monitoring for Trustworthy Retrieval-Augmented Generation
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/xiaowu0162/visualize-then-retrieve
공식 코드https://github.com/xiaoxinhe/g-retriever
공식 코드G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering
https://github.com/xiaoyuan1996/AMFMN
공식 코드Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval
https://github.com/xiaoyuan1996/galr
공식 코드Remote Sensing Cross-Modal Text-Image Retrieval Based on Global and Local Information
https://github.com/xiaoyuan1996/semanticlocalizationmetrics
공식 코드Learning to Evaluate Performance of Multi-modal Semantic Localization
https://github.com/xiaoyuxin1002/sais
공식 코드SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extraction
https://github.com/xid32/naacl_2025_twm
공식 코드Temporal Working Memory: Query-Guided Segment Refinement for Enhanced Multimodal Understanding
https://github.com/xieh97/retrieval-relevance-crowdsourcing
공식 코드Crowdsourcing and Evaluating Text-Based Audio Retrieval Relevances
https://github.com/xingdi-eric-yuan/imrc_public
공식 코드Interactive Machine Comprehension with Information Seeking Agents
https://github.com/xinwei666/mmgenerativeir
공식 코드Generative Multi-Modal Knowledge Retrieval with Large Language Models
https://github.com/xinyadu/rgqa
공식 코드Retrieval-Augmented Generative Question Answering for Event Argument Extraction
https://github.com/xinyiyan/duelingbandits
공식 코드https://github.com/xinzhel/grammar
공식 코드https://github.com/xiweix/reme
공식 코드ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation
https://github.com/xiyanghu/multilingualir
공식 코드Language Agnostic Multilingual Information Retrieval with Contrastive Learning
https://github.com/xlang-ai/arks
공식 코드https://github.com/xmed-lab/iclip
공식 코드Exploring Visual Interpretability for Contrastive Language-Image Pre-training
https://github.com/xmudm/guide-align
공식 코드Ensuring Safe and High-Quality Outputs: A Guideline Library Approach for Language Models
https://github.com/xnliang98/migbert
공식 코드Retrieval-Augmented Classification with Decoupled Representation
https://github.com/xpmir/cosplade
공식 코드CoSPLADE: Contextualizing SPLADE for Conversational Information Retrieval
https://github.com/xqwang14/eva02-at
공식 코드https://github.com/xqwang14/sms-loss
공식 코드Symmetric Multi-Similarity Loss for EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge 2024
https://github.com/xray-grill/didafi_mkcroughan
공식 코드Directional dark-field retrieval with single-grid x-ray imaging
https://github.com/xsc1234/genrt
공식 코드List-aware Reranking-Truncation Joint Model for Search and Retrieval-augmented Generation
https://github.com/xsc1234/info-rag
공식 코드https://github.com/xsc1234/invisible-relevance-bias
공식 코드Invisible Relevance Bias: Text-Image Retrieval Models Prefer AI-Generated Images
https://github.com/xsc1234/match-prompt
공식 코드https://github.com/xsc1234/nir-prompt
공식 코드NIR-Prompt: A Multi-task Generalized Neural Information Retrieval Training Framework
https://github.com/xsc1234/search-in-the-chain
공식 코드https://github.com/xu1998hz/sescore2
공식 코드SESCORE2: Learning Text Generation Evaluation via Synthesizing Realistic Mistakes
https://github.com/xuandongzhao/hpd
공식 코드Compressing Sentence Representation for Semantic Retrieval via Homomorphic Projective Distillation
https://github.com/xuandongzhao/npprompt
공식 코드https://github.com/xuchen0427/fairdiverse
공식 코드FairDiverse: A Comprehensive Toolkit for Fair and Diverse Information Retrieval Algorithms
https://github.com/xuchen0427/fairsync
공식 코드FairSync: Ensuring Amortized Group Exposure in Distributed Recommendation Retrieval
https://github.com/xudonglinthu/upgradable-multimodal-intelligence
공식 코드Towards Fast Adaptation of Pretrained Contrastive Models for Multi-channel Video-Language Retrieval
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.