Papers by Samuel Murphy
KRISTEVA: Close Reading as a Novel Task for Benchmarking Interpretive Reasoning (2025.acl-long)
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Peiqi Sui, Juan Diego Rodriguez, Philippe Laban, J. Dean Murphy, Joseph P. Dexter, Richard Jean So, Samuel Baker, Pramit Chaudhuri
| Challenge: | a study of close reading skills in large language models (LLMs) shows that LLMs still lag behind human evaluators on 10 of 11 tasks. |
| Approach: | They propose a benchmark to evaluate close reading skills in large language models . they propose three tasks to approximate different elements of the close reading process . |
| Outcome: | The proposed benchmarks show that state-of-the-art LLMs possess some college-level close reading competency, but performance still trails human evaluators on 10 out of 11 tasks. |
PATIENT-π: Using Large Language Models to Simulate Patients for Training Mental Health Professionals (2024.emnlp-main)
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Ruiyi Wang, Stephanie Milani, Jamie Chiu, Jiayin Zhi, Shaun Eack, Travis Labrum, Samuel Murphy, Nev Jones, Kate Hardy, Hong Shen, Fei Fang, Zhiyu Chen
| Challenge: | Mental illness remains one of the most critical public health issues. |
| Approach: | They propose a patient simulation framework for cognitive behavior therapy training that uses large language models to act as a simulated therapy patient. |
| Outcome: | The proposed framework improves the skill acquisition and confidence of mental health trainees beyond textbooks, videos, and role-play with non-patients. |