1 citations · 1 across the 13 of their papers we have counts for
13 papers
Implicit vs. Explicit Prompting Strategies for LVLMs in Referential Communication
Peter Zeng, Amie J. Paige, Weiling Li +3
Two recent studies \citep{jones2026llms, zeng2026lvlms} reach apparently contradictory conclusions about whether large vision-language models (LVLMs) can coordinate similarly to hu…
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…
OmniVox: Zero-Shot Emotion Recognition with Omni-LLMs
John Murzaku, Owen Rambow
The use of omni-LLMs (large language models that accept any modality as input), particularly for multimodal cognitive state tasks involving speech, is understudied. We present Omni…
Active Few-Shot Learning for Text Classification
Saeed Ahmadnia, Arash Yousefi Jordehi, Mahsa Hosseini Khasheh Heyran +3
The rise of Large Language Models (LLMs) has boosted the use of Few-Shot Learning (FSL) methods in natural language processing, achieving acceptable performance even when working w…
Zero-Shot Belief: A Hard Problem for LLMs
John Murzaku, Owen Rambow
We present two LLM-based approaches to zero-shot source-and-target belief prediction on FactBank: a unified system that identifies events, sources, and belief labels in a single pa…
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…
Training LLMs to Recognize Hedges in Spontaneous Narratives
Amie J. Paige, Adil Soubki, John Murzaku +2
Hedges allow speakers to mark utterances as provisional, whether to signal non-prototypicality or "fuzziness", to indicate a lack of commitment to an utterance, to attribute respon…
Examining Gender and Power on Wikipedia Through Face and Politeness
Adil Soubki, Shyne Choi, Owen Rambow
We propose a framework for analyzing discourse by combining two interdependent concepts from sociolinguistic theory: face acts and politeness. While politeness has robust existing…
Multimodal Belief Prediction
John Murzaku, Adil Soubki, Owen Rambow
Recognizing a speaker's level of commitment to a belief is a difficult task; humans do not only interpret the meaning of the words in context, but also understand cues from intonat…
Intention and Face in Dialog
Adil Soubki, Owen Rambow
The notion of face described by Brown and Levinson (1987) has been studied in great detail, but a critical aspect of the framework, that which focuses on how intentions mediate the…
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…
Views Are My Own, but Also Yours: Benchmarking Theory of Mind Using Common Ground
Adil Soubki, John Murzaku, Arash Yousefi Jordehi +4
Evaluating the theory of mind (ToM) capabilities of language models (LMs) has recently received a great deal of attention. However, many existing benchmarks rely on synthetic data,…
Finding Common Ground: Annotating and Predicting Common Ground in Spoken Conversations
Magdalena Markowska, Mohammad Taghizadeh, Adil Soubki +2
When we communicate with other humans, we do not simply generate a sequence of words. Rather, we use our cognitive state (beliefs, desires, intentions) and our model of the audienc…