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Text Retrieval
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Text Retrieval is the task of finding the most text result (such as an answer, paragraph, or passage) given a query (which could be a question, keywords, or any relevant text)
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/hchautran/PiToMe
공식 코드Accelerating Transformers with Spectrum-Preserving Token Merging
https://github.com/hondamunigeprasannasilva/attack-attention
공식 코드Attacking Attention of Foundation Models Disrupts Downstream Tasks
https://github.com/hsiehjackson/mr.right
공식 코드Mr. Right: Multimodal Retrieval on Representation of ImaGe witH Text
https://github.com/iigroup/map
공식 코드MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training Model
https://github.com/iigroup/scl
공식 코드Seeing What You Miss: Vision-Language Pre-training with Semantic Completion Learning
https://github.com/ilaria-manco/muscall
공식 코드https://github.com/imirandam/bivlc
공식 코드BiVLC: Extending Vision-Language Compositionality Evaluation with Text-to-Image Retrieval
https://github.com/imirandam/structure-inference-compositionality
공식 코드Adding simple structure at inference improves Vision-Language Compositionality
https://github.com/intersun/LightningDOT
공식 코드LightningDOT: Pre-training Visual-Semantic Embeddings for Real-Time Image-Text Retrieval
https://github.com/islab-github/cdatasets
공식 코드Semantic-Preserving Augmentation for Robust Image-Text Retrieval
https://github.com/ispamm/GRAM
공식 코드https://github.com/j-min/dalleval
공식 코드DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generation Models
https://github.com/jaychempan/pir-clip
공식 코드PIR: Remote Sensing Image-Text Retrieval with Prior Instruction Representation Learning
https://github.com/jerryyli/svitt
공식 코드https://github.com/jetrunner/laprador
공식 코드LaPraDoR: Unsupervised Pretrained Dense Retriever for Zero-Shot Text Retrieval
https://github.com/jinhojsk515/ldmol
공식 코드LDMol: Text-to-Molecule Diffusion Model with Structurally Informative Latent Space
https://github.com/jishengbai/audiosetcaps
공식 코드https://github.com/johncaged/OPT_Questioner
공식 코드Enhancing Vision-Language Pre-Training with Jointly Learned Questioner and Dense Captioner
https://github.com/jssprz/video_captioning_datasets
공식 코드https://github.com/jun-jie-huang/otter
공식 코드Mixed-modality Representation Learning and Pre-training for Joint Table-and-Text Retrieval in OpenQA
https://github.com/junyangwang0410/knight
공식 코드From Association to Generation: Text-only Captioning by Unsupervised Cross-modal Mapping
https://github.com/kid-22/cocktail
공식 코드Cocktail: A Comprehensive Information Retrieval Benchmark with LLM-Generated Documents Integration
https://github.com/kuanghuei/SCAN
공식 코드https://github.com/lancopku/IAIS
공식 코드Learning Relation Alignment for Calibrated Cross-modal Retrieval
https://github.com/lanfeng4659/STR-TDSL
공식 코드Scene Text Retrieval via Joint Text Detection and Similarity Learning
https://github.com/lanfeng4659/pstr
공식 코드https://github.com/layer6ai-labs/fusemix
공식 코드https://github.com/leiluk1/codesearcher
공식 코드https://github.com/leolee99/pau
공식 코드Prototype-based Aleatoric Uncertainty Quantification for Cross-modal Retrieval
https://github.com/lerogo/aaai24_itr_cusa
공식 코드Cross-Modal and Uni-Modal Soft-Label Alignment for Image-Text Retrieval
https://github.com/lezhang7/Enhance-FineGrained
공식 코드https://github.com/lgqu/leaprr
공식 코드https://github.com/libertfan/tags
공식 코드Negative Sample is Negative in Its Own Way: Tailoring Negative Sentences for Image-Text Retrieval
https://github.com/linzhiqiu/visual_gpt_score
공식 코드Revisiting the Role of Language Priors in Vision-Language Models
https://github.com/littleredxh/vse-gradient
공식 코드Dissecting Deep Metric Learning Losses for Image-Text Retrieval
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.