6 papers
Implicit vs. Explicit Prompting Strategies for LVLMs in Referential Communication
Peter Zeng, Amie J. Paige, Weiling Li +3
Two recent studies (Jones et al. (2026); Zeng et al. (2026)) reach apparently contradictory conclusions about whether LVLMs can coordinate on efficient referring expressions. We co…
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…
XAM: Interactive Explainability for Authorship Attribution Models
Milad Alshomary, Anisha Bhatnagar, Peter Zeng +3
We present IXAM, an Interactive eXplainability framework for Authorship Attribution Models. Given an authorship attribution (AA) task and an embedding-based AA model, our tool enab…
Gram2Vec: An Interpretable Document Vectorizer
Peter Zeng, Hannah Stortz, Eric Sclafani +4
We present Gram2Vec, a grammatical style embedding system that embeds documents into a higher dimensional space by extracting the normalized relative frequencies of grammatical fea…
Residualized Similarity for Faithfully Explainable Authorship Verification
Peter Zeng, Pegah Alipoormolabashi, Jihu Mun +5
Responsible use of Authorship Verification (AV) systems not only requires high accuracy but also interpretable solutions. More importantly, for systems to be used to make decisions…
Synthetic Audio Helps for Cognitive State Tasks
Adil Soubki, John Murzaku, Peter Zeng +1
The NLP community has broadly focused on text-only approaches of cognitive state tasks, but audio can provide vital missing cues through prosody. We posit that text-to-speech model…