https://github.com/guoyang9/vqa-prior
공식 코드Quantifying and Alleviating the Language Prior Problem in Visual Question Answering
Papers with Code 아카이브
Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 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/gurdaspuriya/cawa
공식 코드https://github.com/guxm2021/MM_ALT
공식 코드https://github.com/guyrosin/event_driven_qe
공식 코드https://github.com/gwatkinson/jump_download
공식 코드Weakly supervised cross-modal learning in high-content screening
https://github.com/gxym/stgt
공식 코드Video-Language Alignment via Spatio-Temporal Graph Transformer
https://github.com/gyann-z/fdp
공식 코드Focus, Distinguish, and Prompt: Unleashing CLIP for Efficient and Flexible Scene Text Retrieval
https://github.com/gzerveas/CODER
공식 코드https://github.com/h-aldarmaki/sent_translation_retrieval
공식 코드https://github.com/h-peng17/mmet
공식 코드https://github.com/h-tayyarmadabushi/a-frame-semantics-based-approach-for-improved-factual-accuracy-in-large-language-models
공식 코드FS-RAG: A Frame Semantics Based Approach for Improved Factual Accuracy in Large Language Models
https://github.com/h2oai/h2o-llmstudio
공식 코드https://github.com/hackerhyper/acmvh
공식 코드Adaptive Confidence Multi-View Hashing for Multimedia Retrieval
https://github.com/hadjisma/VideoAlignment
공식 코드Representation Learning via Global Temporal Alignment and Cycle-Consistency
https://github.com/hadushhailu/daal-dml
공식 코드DAAL: Density-Aware Adaptive Line Margin Loss for Multi-Modal Deep Metric Learning
https://github.com/haetae-project/hae-rae-bench
공식 코드HAE-RAE Bench: Evaluation of Korean Knowledge in Language Models
https://github.com/hahahawu/vcsum
공식 코드https://github.com/hahnec/plenopticam
공식 코드https://github.com/haixpham/CHEF
공식 코드CHEF: Cross-modal Hierarchical Embeddings for Food Domain Retrieval
https://github.com/haiyangzheng/textgcd
공식 코드Textual Knowledge Matters: Cross-Modality Co-Teaching for Generalized Visual Class Discovery
https://github.com/halueval-wild/halueval-wild
공식 코드HaluEval-Wild: Evaluating Hallucinations of Language Models in the Wild
https://github.com/hamedbabaei/llms4om
공식 코드https://github.com/hamid-amiri/mcdl-image-annotation
공식 코드Toward Real-Time Image Annotation Using Marginalized Coupled Dictionary Learning
https://github.com/hamidehkerdegari/muscle-view-retrieval
공식 코드Automatic retrieval of corresponding US views in longitudinal examinations
https://github.com/hammoudhasan/diffclip
공식 코드https://github.com/hamzeiehsan/questions-to-geosparql
공식 코드https://github.com/hanane-djeddal/attributed-ir
공식 코드An Evaluation Framework for Attributed Information Retrieval using Large Language Models
https://github.com/hanane-djeddal/complex-answer-generation
공식 코드Does Structure Matter? Leveraging Data-to-Text Generation for Answering Complex Information Needs
https://github.com/haneul-yoo/hue
공식 코드HUE: Pretrained Model and Dataset for Understanding Hanja Documents of Ancient Korea
https://github.com/hannibal046/nmt_with_contrastive_memories
공식 코드Neural Machine Translation with Contrastive Translation Memories
https://github.com/hannibal046/pluglm
공식 코드Decouple knowledge from parameters for plug-and-play language modeling
https://github.com/hannibal046/selfmemory
공식 코드Lift Yourself Up: Retrieval-augmented Text Generation with Self Memory
https://github.com/hannight/ramdocs
공식 코드https://github.com/hanpx20/groupdro_dense_retrieval
공식 코드Enhancing Dense Retrievers' Robustness with Group-level Reweighting
https://github.com/hanseokoh/ktrlf
공식 코드https://github.com/hansizeng/cl-drd
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.