https://github.com/kay-wong/Wiki-Reliability
공식 코드Wiki-Reliability: A Large Scale Dataset for Content Reliability on Wikipedia
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/kaz-k/sketch-based-medical-image-retrieval
공식 코드https://github.com/kazuki-irie/kv-memory-brain
공식 코드https://github.com/kdr/videorag-mrr2024
공식 코드Video Enriched Retrieval Augmented Generation Using Aligned Video Captions
https://github.com/kduxin/Bottleneck-Minimal-Indexing
공식 코드Bottleneck-Minimal Indexing for Generative Document Retrieval
https://github.com/kduxin/lmgc
공식 코드https://github.com/kdwonn/DivE
공식 코드Improving Cross-Modal Retrieval with Set of Diverse Embeddings
https://github.com/ke-01/ns-lcr
공식 코드https://github.com/keanudicap/MSQA
공식 코드Empower Large Language Model to Perform Better on Industrial Domain-Specific Question Answering
https://github.com/keflanagan/momentofuntruth
공식 코드Moment of Untruth: Dealing with Negative Queries in Video Moment Retrieval
https://github.com/kelvin-ywc/lpi
공식 코드Low-rank Prompt Interaction for Continual Vision-Language Retrieval
https://github.com/kennymckormick/transrank
공식 코드https://github.com/kent0n-li/chatdoctor
공식 코드https://github.com/kerner-lab/causal-relation-networks
공식 코드An All-MLP Sequence Modeling Architecture That Excels at Copying
https://github.com/keshik6/HourVideo
공식 코드https://github.com/keunwoochoi/Auralisation
공식 코드Explaining Deep Convolutional Neural Networks on Music Classification
https://github.com/keunwoochoi/mir_deepnet_tutorial
공식 코드https://github.com/kevin-rn/Efficient-Fact-checking
공식 코드FlashCheck: Exploration of Efficient Evidence Retrieval for Fast Fact-Checking
https://github.com/kevinjosethomas/sign-language-processing
공식 코드An Open-Source American Sign Language Fingerspell Recognition and Semantic Pose Retrieval Interface
https://github.com/kevinkrahn/ancient-greek-datasets
공식 코드Sentence Embedding Models for Ancient Greek Using Multilingual Knowledge Distillation
https://github.com/kevinliang888/ivr-qa-baselines
공식 코드Simple Baselines for Interactive Video Retrieval with Questions and Answers
https://github.com/kevinlin311tw/Caffe-DeepBinaryCode
공식 코드Supervised Learning of Semantics-Preserving Hash via Deep Convolutional Neural Networks
https://github.com/kevinsrr/unicmr
공식 코드https://github.com/kevinwu23/stanfordclasheval
공식 코드ClashEval: Quantifying the tug-of-war between an LLM's internal prior and external evidence
https://github.com/khalilmrini/medical-question-answering
공식 코드Medical Question Understanding and Answering with Knowledge Grounding and Semantic Self-Supervision
https://github.com/khoadoan/adversarial-hashing
공식 코드Image Hashing by Minimizing Discrete Component-wise Wasserstein Distance
https://github.com/khuangaf/concrete
공식 코드CONCRETE: Improving Cross-lingual Fact-checking with Cross-lingual Retrieval
https://github.com/khui/copacrr
공식 코드Co-PACRR: A Context-Aware Neural IR Model for Ad-hoc Retrieval
https://github.com/khui/repacrr
공식 코드Co-PACRR: A Context-Aware Neural IR Model for Ad-hoc Retrieval
https://github.com/kid-22/cocktail
공식 코드Cocktail: A Comprehensive Information Retrieval Benchmark with LLM-Generated Documents Integration
https://github.com/kid-22/llm-ir-bias-fairness-survey
공식 코드Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Era
https://github.com/kid-22/llm4ir-bias
공식 코드https://github.com/kid-22/source-bias
공식 코드https://github.com/kid-7391/soprc
공식 코드Exploring the Algorithm-Dependent Generalization of AUPRC Optimization with List Stability
https://github.com/kidist-amde/amharic-ir-benchmarks
공식 코드Optimized Text Embedding Models and Benchmarks for Amharic Passage Retrieval
https://github.com/kidist-amde/ddro
공식 코드Lightweight and Direct Document Relevance Optimization for Generative Information Retrieval
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.