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Found 6 papers, 4 papers with code
NeuroPrompts: An Adaptive Framework to Optimize Prompts for Text-to-Image Generation
In this work, we present NeuroPrompts, an adaptive framework that automatically enhances a user's prompt to improve the quality of generations produced by text-to-image models.
ManagerTower: Aggregating the Insights of Uni-Modal Experts for Vision-Language Representation Learning
With only 4M VLP data, ManagerTower achieves superior performances on various downstream VL tasks, especially 79. 15% accuracy on VQAv2 Test-Std, 86. 56% IR@1 and 95. 64% TR@1 on Flickr30K.
MuMUR : Multilingual Multimodal Universal Retrieval
In this paper, we propose a framework MuMUR, that utilizes knowledge transfer from a multilingual model to boost the performance of multi-modal (image and video) retrieval.
BridgeTower: Building Bridges Between Encoders in Vision-Language Representation Learning
Vision-Language (VL) models with the Two-Tower architecture have dominated visual-language representation learning in recent years.
Relation Classification as Two-way Span-Prediction
The current supervised relation classification (RC) task uses a single embedding to represent the relation between a pair of entities.
Ranked #1 on
Relation Extraction
on SemEval-2010 Task-8
Exposing Shallow Heuristics of Relation Extraction Models with Challenge Data
The process of collecting and annotating training data may introduce distribution artifacts which may limit the ability of models to learn correct generalization behavior.
