Search Results for author:
Found 8 papers, 5 papers with code
Successive Subspace Learning: An Overview
Successive Subspace Learning (SSL) offers a light-weight unsupervised feature learning method based on inherent statistical properties of data units (e. g. image pixels and points in point cloud sets).
BERTHop: An Effective Vision-and-Language Model for Chest X-ray Disease Diagnosis
Vision-and-language(V&L) models take image and text as input and learn to capture the associations between them.
Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies
Gender is widely discussed in the context of language tasks and when examining the stereotypes propagated by language models.
GeoMLAMA: Geo-Diverse Commonsense Probing on Multilingual Pre-Trained Language Models
In this paper, we introduce a benchmark dataset, Geo-Diverse Commonsense Multilingual Language Models Analysis (GeoMLAMA), for probing the diversity of the relational knowledge in multilingual PLMs.
MAGIC: Mask-Guided Image Synthesis by Inverting a Quasi-Robust Classifier
We offer a method for one-shot mask-guided image synthesis that allows controlling manipulations of a single image by inverting a quasi-robust classifier equipped with strong regularizers.
How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions?
To this end, we introduce an Ethical NaTural Language Interventions in Text-to-Image GENeration (ENTIGEN) benchmark dataset to evaluate the change in image generations conditional on ethical interventions across three social axes -- gender, skin color, and culture.
Cultural Vocal Bursts Intensity Prediction
Text-to-Image Generation
MetaVL: Transferring In-Context Learning Ability From Language Models to Vision-Language Models
In this paper, we study an interesting hypothesis: can we transfer the in-context learning ability from the language domain to VL domain?
LLMs in Biomedicine: A study on clinical Named Entity Recognition
Large Language Models (LLMs) demonstrate remarkable versatility in various NLP tasks but encounter distinct challenges in biomedicine due to medical language complexities and data scarcity.
