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Chiaroscuro for Emotions: A Contrastive Emotion Benchmark Grounded in Appraisal Theory
Divyesh Bommana, Mohammad Saim, Tianyu Jiang
Emotion recognition benchmarks often predict one emotion per text, missing many real-world scenarios where two people arrive at opposing emotions from a single shared event. For ex…
Emotional Labor Strategy Preferences in LLM Personas
Mohammad Saim, Tianyu Jiang
Emotional labor is the effortful management of emotional displays to meet social or professional expectations. Personality traits have been correlated with emotional labor strategi…
Beyond Supervised Clarification: Input Rewriting with LLMs for Dialogue Discourse Parsing
Yiming Liu, Ziyue Zhang, Zhichao Xu +4
Rewriting inputs to improve frozen downstream models has become a common strategy in modern NLP pipelines. Prior work on incremental dialogue discourse parsing (DDP) shows that sup…
Sycophantic Praise: Evaluating Excessive Praise in Language Models
Daniel Vennemeyer, Phan Anh Duong, Meryl Ye +2
Sycophancy in language models is typically studied as excessive agreement or validation, while explicit praise and flattery have received comparatively little attention. We argue t…
Cross-Lingual Steering for Figurative Language Generation
Linfeng Liu, Tiffany Zhan, Louie Hong Yao +2
Cross-lingual activation steering has been studied mainly for language-agnostic properties such as factual knowledge and reasoning. Its transferability remains unclear for figurati…
Do Emotions Influence Moral Judgment in Large Language Models?
Mohammad Saim, Tianyu Jiang
Large language models have been extensively studied for emotion recognition and moral reasoning as distinct capabilities, yet the extent to which emotions influence moral judgment…
Rhetorical Questions in LLM Representations: A Linear Probing Study
Louie Hong Yao, Vishesh Anand, Yuan Zhuang +1
Rhetorical questions are asked not to seek information but to persuade or signal stance. How large language models internally represent them remains unclear. We analyze rhetorical…
Exploring Concreteness Through a Figurative Lens
Saptarshi Ghosh, Tianyu Jiang
Static concreteness ratings are widely used in NLP, yet a word's concreteness can shift with context, especially in figurative language such as metaphor, where common concrete noun…
MetFuse: Figurative Fusion between Metonymy and Metaphor
Saptarshi Ghosh, Tianyu Jiang
Metonymy and metaphor often co-occur in natural language, yet computational work has studied them largely in isolation. We introduce a framework that transforms a literal sentence…
A Computational Approach to Visual Metonymy
Saptarshi Ghosh, Linfeng Liu, Tianyu Jiang
Images often communicate more than they literally depict: a set of tools can suggest an occupation and a cultural artifact can suggest a tradition. This kind of indirect visual ref…
Anatomy of a Feeling: Narrating Embodied Emotions via Large Vision-Language Models
Mohammad Saim, Phan Anh Duong, Cat Luong +2
The embodiment of emotional reactions from body parts contains rich information about our affective experiences. We propose a framework that utilizes state-of-the-art large vision-…
GuessingGame: Measuring the Informativeness of Open-Ended Questions in Large Language Models
Dylan Hutson, Daniel Vennemeyer, Aneesh Deshmukh +2
We introduce GuessingGame, a protocol for evaluating large language models (LLMs) as strategic question-askers in open-ended, open-domain settings. A Guesser LLM identifies a hidde…
Do LLMs Encode Frame Semantics? Evidence from Frame Identification
Jayanth Krishna Chundru, Rudrashis Poddar, Jie Cao +1
We investigate whether large language models encode latent knowledge of frame semantics, focusing on frame identification, a core challenge in frame semantic parsing that involves…
Sycophancy Is Not One Thing: Causal Separation of Sycophantic Behaviors in LLMs
Daniel Vennemeyer, Phan Anh Duong, Tiffany Zhan +1
Large language models (LLMs) often exhibit sycophantic behaviors -- such as excessive agreement with or flattery of the user -- but it is unclear whether these behaviors arise from…
Evaluating the Impact of Verbal Multiword Expressions on Machine Translation
Linfeng Liu, Saptarshi Ghosh, Tianyu Jiang
Verbal multiword expressions (VMWEs) remain difficult for machine translation because their meanings are often not recoverable from their component words. In this study, we analyze…
Towards Robust Evaluation of Visual Activity Recognition: Resolving Verb Ambiguity with Sense Clustering
Louie Hong Yao, Nicholas Jarvis, Tianyu Jiang
Evaluating visual activity recognition systems is challenging due to inherent ambiguities in verb semantics and image interpretation. When describing actions in images, synonymous…
CHEER-Ekman: Fine-grained Embodied Emotion Classification
Phan Anh Duong, Cat Luong, Divyesh Bommana +1
Emotions manifest through physical experiences and bodily reactions, yet identifying such embodied emotions in text remains understudied. We present an embodied emotion classificat…
ConMeC: A Dataset for Metonymy Resolution with Common Nouns
Saptarshi Ghosh, Tianyu Jiang
Metonymy plays an important role in our daily communication. People naturally think about things using their most salient properties or commonly related concepts. For example, by s…
Classifying Organizations for Food System Ontologies using Natural Language Processing
Tianyu Jiang, Sonia Vinogradova, Nathan Stringham +7
Our research explores the use of natural language processing (NLP) methods to automatically classify entities for the purpose of knowledge graph population and integration with foo…