https://github.com/yuruntian/HyNet
공식 코드HyNet: Learning Local Descriptor with Hybrid Similarity Measure and Triplet Loss
Papers with Code 아카이브
Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 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/yushenli807/www24-rat
공식 코드RAT: Retrieval-Augmented Transformer for Click-Through Rate Prediction
https://github.com/yuweicao-uic/xltime
공식 코드XLTime: A Cross-Lingual Knowledge Transfer Framework for Temporal Expression Extraction
https://github.com/yuwvandy/kg-llm-mdqa
공식 코드Knowledge Graph Prompting for Multi-Document Question Answering
https://github.com/yuxie11/R2D2
공식 코드https://github.com/yuxuan-w/geb-plus
공식 코드GEB+: A Benchmark for Generic Event Boundary Captioning, Grounding and Retrieval
https://github.com/yuyanislearning/CTRL-PG
공식 코드https://github.com/yuyaozhangqaq/query_compiler
공식 코드https://github.com/yuyijiong/hard_retrieval_for_llm
공식 코드Long-context Language Models Cannot Retrieve Without Sufficient Steps
https://github.com/yuzhaouoe/pretraining-data-packing
공식 코드Analysing The Impact of Sequence Composition on Language Model Pre-Training
https://github.com/yuzhimanhua/cof
공식 코드https://github.com/yxKryptonite/RAM_code
공식 코드RAM: Retrieval-Based Affordance Transfer for Generalizable Zero-Shot Robotic Manipulation
https://github.com/yxf203/poisonarena
공식 코드PoisonArena: Uncovering Competing Poisoning Attacks in Retrieval-Augmented Generation
https://github.com/yxgeee/SFRS
공식 코드Self-supervising Fine-grained Region Similarities for Large-scale Image Localization
https://github.com/yxh-y/tablerag
공식 코드TableRAG: A Retrieval Augmented Generation Framework for Heterogeneous Document Reasoning
https://github.com/yyf775/MultiturnFashionRetrieval
공식 코드Conversational Fashion Image Retrieval via Multiturn Natural Language Feedback
https://github.com/yyuncong/tempclr
공식 코드TempCLR: Temporal Alignment Representation with Contrastive Learning
https://github.com/yzleroy/revive
공식 코드REVIVE: Regional Visual Representation Matters in Knowledge-Based Visual Question Answering
https://github.com/yzlianghik2022/ssranking-for-object-ba
공식 코드https://github.com/yzong12138/mvdr_pruning
공식 코드Towards Lossless Token Pruning in Late-Interaction Retrieval Models
https://github.com/zaaachary/csqa-kepr
공식 코드KEPR: Knowledge Enhancement and Plausibility Ranking for Generative Commonsense Question Answering
https://github.com/zafirshi/panovpr
공식 코드https://github.com/zaiwen/cropgpt
공식 코드ShizishanGPT: An Agricultural Large Language Model Integrating Tools and Resources
https://github.com/zbr17/drml
공식 코드https://github.com/zchoi/glscl
공식 코드Text-Video Retrieval with Global-Local Semantic Consistent Learning
https://github.com/zchuz/sigir-mhqa
공식 코드Self-Critique Guided Iterative Reasoning for Multi-hop Question Answering
https://github.com/zefang-liu/TPP-LLM-Embedding
공식 코드Retrieval of Temporal Event Sequences from Textual Descriptions
https://github.com/zefang-liu/tpp-embedding
공식 코드Retrieval of Temporal Event Sequences from Textual Descriptions
https://github.com/zeinabtaghavi/impliret
공식 코드ImpliRet: Benchmarking the Implicit Fact Retrieval Challenge
https://github.com/zeludeng/insclr
공식 코드https://github.com/zengrh3/StructuralMemory
공식 코드https://github.com/zengyan-97/cclm
공식 코드Cross-View Language Modeling: Towards Unified Cross-Lingual Cross-Modal Pre-training
https://github.com/zenquiorra/m3ls
공식 코드https://github.com/zeonchen/sfmgtl
공식 코드Semantic-Fused Multi-Granularity Cross-City Traffic Prediction
https://github.com/zermatt-luo/SBKA
공식 코드Symmetrical Bidirectional Knowledge Alignment for Zero-Shot Sketch-Based Image Retrieval
https://github.com/zeroentropy-cc/legalbenchrag
공식 코드LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.