Search Results for author:
Found 5 papers, 2 papers with code
CML: A Contrastive Meta Learning Method to Estimate Human Label Confidence Scores and Reduce Data Collection Cost
In this paper, we propose a contrastive meta-learning framework (CML) to address the challenges introduced by noisy annotated data, specifically in the context of natural language processing.
ProMISe: Promptable Medical Image Segmentation using SAM
Our experiments demonstrate that such adaptive prompts significantly improve SAM's non-fine-tuned performance in MIS.
Ranked #1 on
Medical Image Segmentation
on ISIC 2018
AbLit: A Resource for Analyzing and Generating Abridged Versions of English Literature
The dataset captures passage-level alignments between the original and abridged texts.
Automated Scoring of Clinical Expressive Language Evaluation Tasks
We find that transfer learning improves scoring accuracy, particularly when using pretrained contextualized embeddings.
A Hybrid Approach Combining Statistical Knowledge with Conditional Random Fields for Chinese Grammatical Error Detection
This paper presents a method of combining Conditional Random Fields (CRFs) model with a post-processing layer using Google n-grams statistical information tailored to detect word selection and word order errors made by learners of Chinese as Foreign Language (CFL).
