6 citations · 11 across the 6 of their papers we have counts for
7 papers
Modeling the Developmental Shift in Telicity Acquisition
Ellie Xia, Parisa Kordjamshidi, Alan Hezao Ke
Acquiring telicity, which is the distinction between bounded (e.g., ate an apple) and unbounded (e.g., ate apples) events, requires first language (L1) learners to map surface-leve…
Do Vision-Language Models Represent Space and How? Evaluating Spatial Frame of Reference Under Ambiguities
Zheyuan Zhang, Fengyuan Hu, Jayjun Lee +4
Spatial expressions in situated communication can be ambiguous, as their meanings vary depending on the frames of reference (FoR) adopted by speakers and listeners. While spatial l…
Vision-and-Language Navigation Today and Tomorrow: A Survey in the Era of Foundation Models
Yue Zhang, Ziqiao Ma, Jialu Li +6
Vision-and-Language Navigation (VLN) has gained increasing attention over recent years and many approaches have emerged to advance their development. The remarkable achievements of…
GIPCOL: Graph-Injected Soft Prompting for Compositional Zero-Shot Learning
Guangyue Xu, Joyce Chai, Parisa Kordjamshidi
Pre-trained vision-language models (VLMs) have achieved promising success in many fields, especially with prompt learning paradigm. In this work, we propose GIP-COL (Graph-Injected…
MetaReVision: Meta-Learning with Retrieval for Visually Grounded Compositional Concept Acquisition
Guangyue Xu, Parisa Kordjamshidi, Joyce Chai
Humans have the ability to learn novel compositional concepts by recalling and generalizing primitive concepts acquired from past experiences. Inspired by this observation, in this…
Prompting Large Pre-trained Vision-Language Models For Compositional Concept Learning
Guangyue Xu, Parisa Kordjamshidi, Joyce Chai
This work explores the zero-shot compositional learning ability of large pre-trained vision-language models(VLMs) within the prompt-based learning framework and propose a model (\t…
Zero-Shot Compositional Concept Learning
Guangyue Xu, Parisa Kordjamshidi, Joyce Y. Chai
In this paper, we study the problem of recognizing compositional attribute-object concepts within the zero-shot learning (ZSL) framework. We propose an episode-based cross-attentio…