Papers with Code 아카이브
Information Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
- 33
- 보존된 평가 기록
- 17
Information retrieval is the task of ranking a list of documents or search results in response to a query
<span style="color:grey; opacity: 0.6">( Image credit: sudhanshumittal )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/hltcoe/psq
공식 코드https://github.com/hmthanh/GCAT
공식 코드Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs
https://github.com/hobbitqia/unimoco
공식 코드UniMoCo: Unified Modality Completion for Robust Multi-Modal Embeddings
https://github.com/hohsiangwu/crossmodal
공식 코드Exploring modality-agnostic representations for music classification
https://github.com/hoplee6/sports-qa
공식 코드Sports-QA: A Large-Scale Video Question Answering Benchmark for Complex and Professional Sports
https://github.com/hou27/recdap-fkgc
공식 코드https://github.com/hpclab/efficient_nn_for_ltr
공식 코드https://github.com/hpclab/toploc_conv_search
공식 코드Efficient Conversational Search via Topical Locality in Dense Retrieval
https://github.com/hsiehjackson/mr.right
공식 코드Mr. Right: Multimodal Retrieval on Representation of ImaGe witH Text
https://github.com/huggingface/gaia
공식 코드GAIA Search: Hugging Face and Pyserini Interoperability for NLP Training Data Exploration
https://github.com/huggingface/transformers
공식 코드https://github.com/hugochan/BAMnet
공식 코드Bidirectional Attentive Memory Networks for Question Answering over Knowledge Bases
https://github.com/huiguanlab/rpf
공식 코드https://github.com/husseinmozannar/SOQAL
공식 코드https://github.com/hymie122/rag-survey
공식 코드Retrieval-Augmented Generation for AI-Generated Content: A Survey
https://github.com/iai-group/cast-snippets
공식 코드https://github.com/iai-group/sigir2024-multi-query-rewriting
공식 코드https://github.com/ibm-aur-nlp/PubTabNet
공식 코드https://github.com/ibm-ecosystem-engineering/blended-rag
공식 코드https://github.com/ibm/kgi-slot-filling
공식 코드Robust Retrieval Augmented Generation for Zero-shot Slot Filling
https://github.com/ibm/tabsketchfm
공식 코드TabSketchFM: Sketch-based Tabular Representation Learning for Data Discovery over Data Lakes
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/tara
공식 코드Topic-oriented Adversarial Attacks against Black-box Neural Ranking Models
https://github.com/idea-finai/tog-2
공식 코드https://github.com/ielab/2dmse-reproduce
공식 코드https://github.com/ielab/agvaluate
공식 코드AgAsk: An Agent to Help Answer Farmer's Questions From Scientific Documents
https://github.com/ielab/asyncval
공식 코드Asyncval: A Toolkit for Asynchronously Validating Dense Retriever Checkpoints during Training
https://github.com/ielab/characterbert-dr
공식 코드https://github.com/ielab/counterfactual-dr
공식 코드Implicit Feedback for Dense Passage Retrieval: A Counterfactual Approach
https://github.com/ielab/dense-screening-feedback
공식 코드Dense Retrieval with Continuous Explicit Feedback for Systematic Review Screening Prioritisation
https://github.com/ielab/goldilocks-reproduce
공식 코드A Reproducibility Study of Goldilocks: Just-Right Tuning of BERT for TAR
https://github.com/ielab/green-ir
공식 코드Beyond CO2 Emissions: The Overlooked Impact of Water Consumption of Information Retrieval Models
https://github.com/ielab/llm-qlm
공식 코드Open-source Large Language Models are Strong Zero-shot Query Likelihood Models for Document Ranking
https://github.com/ielab/non-iid-foltr
공식 코드Is Non-IID Data a Threat in Federated Online Learning to Rank?
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.