Papers by Gerard Christopher Yeo
Learning Through Dialogue: Engagement and Efficacy Matter More Than Explanations (2026.findings-acl)
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| Challenge: | Large language models (LLMs) are increasingly used as conversational partners for learning, yet the interactional dynamics supporting users’ learning and engagement are understudied. |
| Approach: | They analyze linguistic and interactional features from LLM and participant chats to identify the mechanisms and conditions under which LLM explanations shape changes in political knowledge and confidence. |
| Outcome: | The results show that LLM explanations shape political knowledge and confidence . they also show that their effects are highly conditional and vary by political efficacy . |
Beyond Context to Cognitive Appraisal: Emotion Reasoning as a Theory of Mind Benchmark for Large Language Models (2025.findings-acl)
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| Challenge: | Recent studies have shown that large language models (LLMs) reason about others' emotional states using contextual information, within a Theory-of-Mind framework. |
| Approach: | They propose to use large language models to reason about others’ emotional states using contextual information within a Theory-of-Mind framework. |
| Outcome: | The proposed models can reason about situations and appraisals, but are poor at associating situational outcomes and appraisal with specific emotions. |