https://github.com/beir-cellar/beir
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models
Papers with Code 아카이브
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/bojone/labse
https://github.com/bwconrad/flexivit
https://github.com/caijincen712/CE
Learning a Text-Video Embedding from Incomplete and Heterogeneous Data
https://github.com/castorini/Anserini
BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval
https://github.com/chendelong1999/subobjects
One Trajectory, One Token: Grounded Video Tokenization via Panoptic Sub-object Trajectory
https://github.com/chenghaomou/text-dedup
https://github.com/chiyeunglaw/lexlip-iccv23
LexLIP: Lexicon-Bottlenecked Language-Image Pre-Training for Large-Scale Image-Text Retrieval
https://github.com/climsocana/tecb-de
https://github.com/clip-italian/clip-italian
WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning
https://github.com/conda-forge/bm25s-feedstock
BM25S: Orders of magnitude faster lexical search via eager sparse scoring
https://github.com/cshizhe/hgr_v2t
Fine-grained Video-Text Retrieval with Hierarchical Graph Reasoning
https://github.com/emory-irlab/pyterrier_genrank
https://github.com/escorciav/Mixture-of-Embedding-Experts
Learning a Text-Video Embedding from Incomplete and Heterogeneous Data
https://github.com/evelinehong/VLGrammar
VLGrammar: Grounded Grammar Induction of Vision and Language
https://github.com/facebookresearch/DPR
Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering
https://github.com/facebookresearch/EgoTV
CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval
https://github.com/facebookresearch/ParlAI
https://github.com/facebookresearch/metaclip
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
https://github.com/facebookresearch/multimodal
Align before Fuse: Vision and Language Representation Learning with Momentum Distillation
https://github.com/fmenat/DiscreteVAE
https://github.com/grill-lab/codec
Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval
https://github.com/h2oai/h2ogpt
https://github.com/hbzhang/cvpr2020
Learning a Text-Video Embedding from Incomplete and Heterogeneous Data
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/idejie/SCAN
https://github.com/jayleicn/TVRetrieval
Learning a Text-Video Embedding from Incomplete and Heterogeneous Data
https://github.com/jeongukjae/smaller-labse
https://github.com/jielin-qiu/mm_robustness
Benchmarking Robustness of Multimodal Image-Text Models under Distribution Shift
https://github.com/joe-prog/https-github.com-facebookresearch-ParlAI
https://github.com/kakaobrain/coyo-dataset
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
https://github.com/kakaobrain/rq-vae-transformer
DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generation Models
https://github.com/layer6ai-labs/direct-cms
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.