Search Results for author:
Found 6 papers, 4 papers with code
The Application of ChatGPT in Responding to Questions Related to the Boston Bowel Preparation Scale
This study aims to assess the accuracy and consistency of ChatGPT in using the Boston Bowel Preparation Scale (BBPS) for colonoscopy assessment.
Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models
To address this limitation and prioritize harnessing structured knowledge, this paper advocates for leveraging LLMs to build a graph for each description to model the entities and attributes describing the category, as well as their correlations.
Ranked #1 on
Prompt Engineering
on ImageNet V2
Exploring Shape Embedding for Cloth-Changing Person Re-Identification via 2D-3D Correspondences
CSCL establishes continuous correspondences between a 2D image plane and a canonical 3D body surface via pixel-to-vertex classification, which naturally aligns a person image to the surface of a 3D human model and simultaneously obtains pixel-wise surface embeddings.
Learning Domain Invariant Prompt for Vision-Language Models
Prompt learning is one of the most effective and trending ways to adapt powerful vision-language foundation models like CLIP to downstream datasets by tuning learnable prompt vectors with very few samples.
Ranked #4 on
Prompt Engineering
on Caltech-101
Few-Shot Event Detection with Prototypical Amortized Conditional Random Field
Event detection tends to struggle when it needs to recognize novel event types with a few samples.
Joint Extraction of Entities and Relations Based on a Novel Decomposition Strategy
Joint extraction of entities and relations aims to detect entity pairs along with their relations using a single model.
Ranked #1 on
Relation Extraction
on NYT-single
