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Text Retrieval

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평가표: 16
보존된 평가 기록: 51

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/ckdjrkffz/multi-stage-reranking

공식 코드

Text Retrieval with Multi-Stage Re-Ranking Models

https://github.com/codezakh/SIMLA

공식 코드

Single-Stream Multi-Level Alignment for Vision-Language Pretraining

https://github.com/computer-vision-in-the-wild/cvinw_readings

공식 코드

Vision-Language Pre-training: Basics, Recent Advances, and Future Trends

https://github.com/control-xl/medical-vision-langauge-transformer

공식 코드

Multi-modal Pre-training for Medical Vision-language Understanding and Generation: An Empirical Study with A New Benchmark

https://github.com/cwj1412/mscoco-flikcr30k_fg

공식 코드

Rethinking Benchmarks for Cross-modal Image-text Retrieval

https://github.com/datascienceuibk/arabicaqa

공식 코드

ArabicaQA: A Comprehensive Dataset for Arabic Question Answering

https://github.com/deep-polyu/awesome-graphrag

공식 코드

A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models

https://github.com/deepglint/alip

공식 코드

ALIP: Adaptive Language-Image Pre-training with Synthetic Caption

https://github.com/deepglint/rwkv-clip

공식 코드

RWKV-CLIP: A Robust Vision-Language Representation Learner

https://github.com/deepglint/unicom

공식 코드

Multi-label Cluster Discrimination for Visual Representation Learning

https://github.com/deepmind/deepmind-research/tree/master/wikigraphs

공식 코드

WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Dataset

https://github.com/dell-research-harvard/linktransformer

공식 코드

LinkTransformer: A Unified Package for Record Linkage with Transformer Language Models

https://github.com/deokhk/dotter

공식 코드

Denoising Table-Text Retrieval for Open-Domain Question Answering

https://github.com/dopaminelcy/alta

공식 코드

Efficient Medical Vision-Language Alignment Through Adapting Masked Vision Models

https://github.com/eanson023/rehamot

공식 코드

Cross-Modal Retrieval for Motion and Text via DopTriple Loss

https://github.com/ellenzhuwang/VK_OOD

공식 코드

Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis

https://github.com/embeddings-benchmark/mteb

공식 코드

MTEB: Massive Text Embedding Benchmark

https://github.com/eric-ai-lab/comclip

공식 코드

ComCLIP: Training-Free Compositional Image and Text Matching

https://github.com/facebookresearch/meru

공식 코드

Hyperbolic Image-Text Representations

https://github.com/fangkaipeng/pros

공식 코드

ProS: Prompting-to-simulate Generalized knowledge for Universal Cross-Domain Retrieval

https://github.com/farewellthree/stan

공식 코드

Revisiting Temporal Modeling for CLIP-based Image-to-Video Knowledge Transferring

https://github.com/felixvogel02/vl-taboo

공식 코드

VL-Taboo: An Analysis of Attribute-based Zero-shot Capabilities of Vision-Language Models

https://github.com/flageval-baai/flagevalmm

공식 코드

FlagEvalMM: A Flexible Framework for Comprehensive Multimodal Model Evaluation

https://github.com/flair-thu/creamfl

공식 코드

Multimodal Federated Learning via Contrastive Representation Ensemble

https://github.com/fundamentalvision/Uni-Perceiver

공식 코드

Uni-Perceiver-MoE: Learning Sparse Generalist Models with Conditional MoEs

https://github.com/gengyuanmax/mevtr

공식 코드

Multi-event Video-Text Retrieval

https://github.com/google-research-datasets/wit

공식 코드

WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning

https://github.com/google-research/big_vision

공식 코드

FlexiViT: One Model for All Patch Sizes

https://github.com/google-research/google-research/tree/master/fvlm/rovit

공식 코드

Region-Aware Pretraining for Open-Vocabulary Object Detection with Vision Transformers

https://github.com/google-research/google-research/tree/master/socraticmodels

공식 코드

Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language

https://github.com/google-research/language/tree/master/language/multivec

공식 코드

Sparse, Dense, and Attentional Representations for Text Retrieval

https://github.com/google/unisim

공식 코드

RETSim: Resilient and Efficient Text Similarity

https://github.com/gregor-ge/babel-imagenet

공식 코드

Babel-ImageNet: Massively Multilingual Evaluation of Vision-and-Language Representations

https://github.com/gxym/stgt

공식 코드

Video-Language Alignment via Spatio-Temporal Graph Transformer

https://github.com/gyann-z/fdp

공식 코드

Focus, Distinguish, and Prompt: Unleashing CLIP for Efficient and Flexible Scene Text Retrieval

https://github.com/gzerveas/CODER

공식 코드

Enhancing the Ranking Context of Dense Retrieval Methods through Reciprocal Nearest Neighbors

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.