https://github.com/Heidelberg-NLP/discourse-aware-semantic-self-attention
Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering
Papers with Code 아카이브
Text Matching
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Matching a target text to a source text based on their meaning.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/JingfenQiao/ColPali-Reproducibility
ColPali: Efficient Document Retrieval with Vision Language Models
https://github.com/JunweiLiang/DualAttentionNetwork
Dual Attention Networks for Multimodal Reasoning and Matching
https://github.com/Maymaher/StackGANv2
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/MindSpore-scientific-2/code-10/tree/main/PolyLoss
Universal Weighting Metric Learning for Cross-Modal Matching
https://github.com/MysteryVaibhav/SCAN
https://github.com/PaddlePaddle/PaddleRec/tree/release/2.1.0/models/match/match-pyramid
https://github.com/Riadh-B/MTFN-RR-PyTorch-Code-master
Matching Images and Text with Multi-modal Tensor Fusion and Re-ranking
https://github.com/SDLZY/VCR_Align
https://github.com/SJHBXShub/Question_pair
https://github.com/Shuvrajit9904/PairedCycleGAN-tf
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/Vigneshthanga/stackGAN-v2
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/YIKUAN8/Transformers-VQA
https://github.com/abhidipbhattacharyya/srl_aware_ret
https://github.com/abhijeet3922/vision-RAG
ColPali: Efficient Document Retrieval with Vision Language Models
https://github.com/adlnlp/attention_vl
https://github.com/albpurpura/PE4IR
https://github.com/aleksey-egorov/attngan
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/alexmotogna/attngan
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/alexmotogna/generatorapi
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/alibaba-edu/simple-effective-text-matching
Simple and Effective Text Matching with Richer Alignment Features
https://github.com/alibaba-edu/simple-effective-text-matching-pytorch
Simple and Effective Text Matching with Richer Alignment Features
https://github.com/aranciokov/fsmmda_videoretrieval
Fine-grained Video-Text Retrieval with Hierarchical Graph Reasoning
https://github.com/aranciokov/ranp
Fine-grained Video-Text Retrieval with Hierarchical Graph Reasoning
https://github.com/asif-hanif/baple
A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models
https://github.com/bprabhakar/text-to-image
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/cshizhe/hgr_v2t
Fine-grained Video-Text Retrieval with Hierarchical Graph Reasoning
https://github.com/davidstap/AttnGAN
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/facebookresearch/DPR
Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering
https://github.com/hongyuntw/DPR
Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering
https://github.com/hongyuntw/DPR_BESS
Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering
https://github.com/hthoai/image-text-matching
https://github.com/huggingface/transformers
Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering
https://github.com/huiyegit/T2I_CL
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/iammrhelo/pytorch-vqa-dan
Dual Attention Networks for Multimodal Reasoning and Matching
https://github.com/idejie/SCAN
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.