My research group:

Overarching Research Themes

*Extracted by GPT-4, there may be inconsistencies.* #### *Ethics and Responsible AI* My research group explores the ethical implications of AI technologies, focusing on bias and fairness in language models. Significant studies include [Disparities in LLM Reasoning Accuracy and Explanations: A Case Study on African American English](https://arxiv.org/abs/2503.04099), which highlights discrepancies in reasoning based on dialect, and [Mitigating Bias in RAG: Controlling the Embedder](https://arxiv.org/abs/2502.17390), emphasizing techniques to address biases in retrieval-augmented generation. Additionally, our work on [Mind the Gesture: Evaluating AI Sensitivity to Culturally Offensive Non-Verbal Gestures](https://arxiv.org/abs/2502.17710) showcases the importance of non-verbal communication in AI interactions, stressing the need for cultural awareness in AI systems. #### *Exploring Social Dynamics in AI* My research group explores the social intelligence of AI agents and their interactions within dynamic environments. The paper [SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents](https://arxiv.org/abs/2310.11667) discusses methodologies for assessing AI's understanding of social cues. Our research also includes [Is This the Real Life? Is This Just Fantasy? The Misleading Success of Simulating Social Interactions With LLMs](http://arxiv.org/abs/2403.05020), which critiques the effectiveness of simulated interactions. Furthermore, we investigate [Clever Hans or Neural Theory of Mind? Stress Testing Social Reasoning in Large Language Models](https://arxiv.org/abs/2305.14763) to evaluate the limitations of social reasoning in AI. #### *Narrative Analysis and Storytelling* My research group explores the role of narratives in understanding human experiences and their interaction with AI. Our important work includes [Quantifying the narrative flow of imagined versus autobiographical stories](https://www.pnas.org/doi/10.1073/pnas.2211715119), which examines how stories are perceived differently depending on their origin. In addition, we delve into [HEART-felt Narratives: Tracing Empathy and Narrative Style in Personal Stories with LLMs](https://arxiv.org/abs/2405.17633), highlighting the emotional resonance of storytelling when mediated by AI. The paper [The Empirical Variability of Narrative Perceptions of Social Media Texts](https://aclanthology.org/2024.emnlp-main.1113/) further emphasizes the diverse interpretations of narratives in contemporary contexts. #### *Mitigating Toxic Language in AI* My research group explores methods to reduce the prevalence of toxic language produced by AI systems. One key study is [PolygloToxicityPrompts: Multilingual Evaluation of Neural Toxic Degeneration in Large Language Models](https://arxiv.org/abs/2405.09373), which investigates bias in language models across different languages. Additionally, our research addresses user experiences in combating online hate with [Counterspeakers’ Perspectives: Unveiling Barriers and AI Needs in the Fight against Online Hate](https://arxiv.org/abs/2403.00179), focusing on the practical application of AI in fostering safer online environments. We also analyze [COBRA Frames: Contextual Reasoning about Effects and Harms of Offensive Statements](http://arxiv.org/abs/2306.01985), which underscores the need for contextual sensitivity in AI language generation.