https://github.com/nlpcode/annollm
공식 코드AnnoLLM: Making Large Language Models to Be Better Crowdsourced Annotators
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/nnnoidea/stateful-KGQA
공식 코드https://github.com/noah888/dar
공식 코드Enhancing Recipe Retrieval with Foundation Models: A Data Augmentation Perspective
https://github.com/noahsark/dada
공식 코드Towards Improved Proxy-based Deep Metric Learning via Data-Augmented Domain Adaptation
https://github.com/noakliu/graphsnapshot
공식 코드GraphSnapShot: Caching Local Structure for Fast Graph Learning
https://github.com/nobrowning/seq_hgnn
공식 코드Seq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph
https://github.com/noen61/mvd
공식 코드Towards Better Entity Linking with Multi-View Enhanced Distillation
https://github.com/noewangjy/csprd_dataset
공식 코드CSPRD: A Financial Policy Retrieval Dataset for Chinese Stock Market
https://github.com/nohtow/wtf-rl
공식 코드Distinctive Image Captioning: Leveraging Ground Truth Captions in CLIP Guided Reinforcement Learning
https://github.com/nokia/codesearch
공식 코드Neural Code Search Revisited: Enhancing Code Snippet Retrieval through Natural Language Intent
https://github.com/nomothings/charge
공식 코드Benchmarking Multimodal RAG through a Chart-based Document Question-Answering Generation Framework
https://github.com/nopperl/clip_arxiv_pmc
공식 코드https://github.com/norakassner/BERT-kNN
공식 코드BERT-kNN: Adding a kNN Search Component to Pretrained Language Models for Better QA
https://github.com/normal-computing/extended-mind-transformers
공식 코드https://github.com/notonion/chartthinker
공식 코드ChartThinker: A Contextual Chain-of-Thought Approach to Optimized Chart Summarization
https://github.com/novasearch-team/rag-retrieval
공식 코드Benchmarking the Myopic Trap: Positional Bias in Information Retrieval
https://github.com/novasearch/conversational-search-assistant-transformers
공식 코드Open-Domain Conversational Search Assistant with Transformers
https://github.com/nshubham655/RUDDER
공식 코드https://github.com/nthakur20/income
공식 코드https://github.com/nttcslab/apwd-dataset
공식 코드Introducing Auxiliary Text Query-modifier to Content-based Audio Retrieval
https://github.com/ntunlp/kmlm
공식 코드Enhancing Multilingual Language Model with Massive Multilingual Knowledge Triples
https://github.com/ntunlp/xCodeEval
공식 코드https://github.com/nu-c3lab/satyrn
공식 코드https://github.com/nuochenpku/comedy
공식 코드https://github.com/nuochenpku/harry-potter-dialogue-dataset
공식 코드https://github.com/nus-hpc-ai-lab/multimodal-icl-retriever
공식 코드How Does the Textual Information Affect the Retrieval of Multimodal In-Context Learning?
https://github.com/nvidia-merlin/hugectr
공식 코드A GPU-specialized Inference Parameter Server for Large-Scale Deep Recommendation Models
https://github.com/nvlabs/palavra
공식 코드"This is my unicorn, Fluffy": Personalizing frozen vision-language representations
https://github.com/nvlabs/pervlbenchmark
공식 코드"This is my unicorn, Fluffy": Personalizing frozen vision-language representations
https://github.com/nvlabs/retmol
공식 코드https://github.com/nyu-dl/dl4ir-doc2query
공식 코드https://github.com/nyu-dl/dl4marco-bert
공식 코드https://github.com/nyuolab/MedMobile
공식 코드MedMobile: A mobile-sized language model with expert-level clinical capabilities
https://github.com/nzjin/odtqa
공식 코드Enhancing Open-Domain Table Question Answering via Syntax- and Structure-aware Dense Retrieval
https://github.com/oaqa/FlexNeuART
공식 코드https://github.com/oatml-markslab/tranception
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.