no code implementations • 22 May 2024 • Ziqiao Ma, Zekun Wang, Joyce Chai
In this work, we aim to examine how corrective feedback from interactions influences neural language acquisition from the ground up through systematically controlled experiments, assessing whether it contributes to learning efficiency in language models.
no code implementations • 26 Feb 2024 • Yichi Zhang, Ziqiao Ma, Xiaofeng Gao, Suhaila Shakiah, Qiaozi Gao, Joyce Chai
Most multimodal large language models (MLLMs) learn language-to-object grounding through causal language modeling where grounded objects are captured by bounding boxes as sequences of location tokens.
Ranked #2 on Generalized Referring Expression Segmentation on gRefCOCO (using extra training data)
Causal Language Modeling Generalized Referring Expression Segmentation +2
1 code implementation • 7 Dec 2023 • Sihan Xu, Yidong Huang, Jiayi Pan, Ziqiao Ma, Joyce Chai
We show that when the initial sample is known, a special variance schedule reduces the denoising step to the same form as the multi-step consistency sampling.
Ranked #1 on Text-based Image Editing on PIE-Bench
1 code implementation • 30 Oct 2023 • Ziqiao Ma, Jacob Sansom, Run Peng, Joyce Chai
Such situated evaluation provides a more comprehensive assessment of mental states and potentially mitigates the risk of shortcuts and data leakage.
1 code implementation • NeurIPS 2023 • Sihan Xu, Ziqiao Ma, Yidong Huang, Honglak Lee, Joyce Chai
Our empirical studies show that Cyclenet is superior in translation consistency and quality, and can generate high-quality images for out-of-domain distributions with a simple change of the textual prompt.
1 code implementation • 14 Jun 2023 • Ziqiao Ma, Jiayi Pan, Joyce Chai
The ability to connect language units to their referents in the physical world, referred to as grounding, is crucial to learning and understanding grounded meanings of words.
3 code implementations • 26 May 2023 • Shane Storks, Keunwoo Peter Yu, Ziqiao Ma, Joyce Chai
As natural language processing (NLP) has recently seen an unprecedented level of excitement, and more people are eager to enter the field, it is unclear whether current research reproducibility efforts are sufficient for this group of beginners to apply the latest developments.
1 code implementation • 18 May 2023 • Cristian-Paul Bara, Ziqiao Ma, Yingzhuo Yu, Julie Shah, Joyce Chai
To complete these tasks, agents need to engage in situated communication with their partners and coordinate their partial plans towards a complete plan to achieve a joint task goal.
1 code implementation • 22 Oct 2022 • Yichi Zhang, Jianing Yang, Jiayi Pan, Shane Storks, Nikhil Devraj, Ziqiao Ma, Keunwoo Peter Yu, Yuwei Bao, Joyce Chai
These reactive agents are insufficient for long-horizon complex tasks.
1 code implementation • 22 Oct 2022 • Ziqiao Ma, Ben VanDerPloeg, Cristian-Paul Bara, Huang Yidong, Eui-In Kim, Felix Gervits, Matthew Marge, Joyce Chai
To this end, we introduce Dialogue On the ROad To Handle Irregular Events (DOROTHIE), a novel interactive simulation platform that enables the creation of unexpected situations on the fly to support empirical studies on situated communication with autonomous driving agents.
1 code implementation • 23 Jan 2022 • Jiaqi Ma, Ziqiao Ma, Joyce Chai, Qiaozhu Mei
We study the problem of semi-supervised learning with Graph Neural Networks (GNNs) in an active learning setup.