https://github.com/iaar-shanghai/saferag
공식 코드SafeRAG: Benchmarking Security in Retrieval-Augmented Generation of Large Language Model
Papers with Code 아카이브
Retrieval
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- 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/iacercalixto/visualsem
공식 코드VisualSem: A High-quality Knowledge Graph for Vision and Language
https://github.com/iago-suarez/beblid
공식 코드https://github.com/iai-group/cast-snippets
공식 코드https://github.com/iai-group/ginger-response-generation
공식 코드GINGER: Grounded Information Nugget-Based Generation of Responses
https://github.com/iai-group/sigir2019-table2vec
공식 코드Table2Vec: Neural Word and Entity Embeddings for Table Population and Retrieval
https://github.com/iai-group/sigir2024-multi-query-rewriting
공식 코드https://github.com/iai-group/table-retrieval
공식 코드https://github.com/iai-group/www2018-table
공식 코드https://github.com/iamhankai/attribute-aware-attention
공식 코드Attribute-Aware Attention Model for Fine-grained Representation Learning
https://github.com/iapalm/Spoken-ObjectNet
공식 코드https://github.com/ibm-aur-nlp/PubTabNet
공식 코드https://github.com/ibm-ecosystem-engineering/blended-rag
공식 코드https://github.com/ibm-hyperknowledge/mlwfm
공식 코드https://github.com/ibm/kgi-slot-filling
공식 코드Robust Retrieval Augmented Generation for Zero-shot Slot Filling
https://github.com/ibm/mt-rag-benchmark
공식 코드MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation Systems
https://github.com/ibm/remote-sensing-image-retrieval
공식 코드Multi-Spectral Remote Sensing Image Retrieval Using Geospatial Foundation Models
https://github.com/ibm/retrieval-table-augmentation
공식 코드https://github.com/ibrahimethemhamamci/ct-clip
공식 코드Developing Generalist Foundation Models from a Multimodal Dataset for 3D Computed Tomography
https://github.com/icip-cas/selfretrieval
공식 코드Self-Retrieval: End-to-End Information Retrieval with One Large Language Model
https://github.com/ict-bigdatalab/certdr
공식 코드Certified Robustness to Word Substitution Ranking Attack for Neural Ranking Models
https://github.com/ict-bigdatalab/clever
공식 코드Continual Learning for Generative Retrieval over Dynamic Corpora
https://github.com/ict-bigdatalab/corpusbrain
공식 코드CorpusBrain: Pre-train a Generative Retrieval Model for Knowledge-Intensive Language Tasks
https://github.com/ict-bigdatalab/fer
공식 코드From Relevance to Utility: Evidence Retrieval with Feedback for Fact Verification
https://github.com/ict-bigdatalab/rc-rag
공식 코드Controlling Risk of Retrieval-augmented Generation: A Counterfactual Prompting Framework
https://github.com/ict-bigdatalab/right
공식 코드RIGHT: Retrieval-augmented Generation for Mainstream Hashtag Recommendation
https://github.com/ict-bigdatalab/tara
공식 코드Topic-oriented Adversarial Attacks against Black-box Neural Ranking Models
https://github.com/ict-bigdatalab/ugr
공식 코드A Unified Generative Retriever for Knowledge-Intensive Language Tasks via Prompt Learning
https://github.com/ict-bigdatalab/utility_judgments
공식 코드https://github.com/ict-bigdatalab/vnel
공식 코드https://github.com/ictnlp/LevelRAG
공식 코드https://github.com/ictnlp/auto-rag
공식 코드Auto-RAG: Autonomous Retrieval-Augmented Generation for Large Language Models
https://github.com/ictnlp/flexrag
공식 코드FlexRAG: A Flexible and Comprehensive Framework for Retrieval-Augmented Generation
https://github.com/ictnlp/pluvr
공식 코드Neural Machine Translation with Phrase-Level Universal Visual Representations
https://github.com/idea-finai/ragllava
공식 코드https://github.com/idea-finai/ragvl
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.