4 papers · 1 filter
LVLMs and Humans Ground Differently in Referential Communication
Peter Zeng, Weiling Li, Amie J. Paige +6
For generative AI agents to partner effectively with human users, the ability to accurately predict human intent is critical. But this ability to collaborate remains limited by a c…
LVLMs are Bad at Overhearing Human Referential Communication
Zhengxiang Wang, Weiling Li, Panagiotis Kaliosis +2
During spontaneous conversations, speakers collaborate on novel referring expressions, which they can then re-use in subsequent conversations. Understanding such referring expressi…
LLMs can Perform Multi-Dimensional Analytic Writing Assessments: A Case Study of L2 Graduate-Level Academic English Writing
Zhengxiang Wang, Veronika Makarova, Zhi Li +2
The paper explores the performance of LLMs in the context of multi-dimensional analytic writing assessments, i.e. their ability to provide both scores and comments based on multipl…
Clustering Document Parts: Detecting and Characterizing Influence Campaigns from Documents
Zhengxiang Wang, Owen Rambow
We propose a novel clustering pipeline to detect and characterize influence campaigns from documents. This approach clusters parts of document, detects clusters that likely reflect…