PsychoLex: Unveiling the Psychological Mind of Large Language Models

• URL: http://arxiv.org/abs/2408.08848v1
• Date: Fri, 16 Aug 2024 17:19:23 GMT
• Title: PsychoLex: Unveiling the Psychological Mind of Large Language Models
• Authors: Mohammad Amin Abbasi, Farnaz Sadat Mirnezami, Hassan Naderi,
• Abstract summary: This paper explores the intersection of psychology and artificial intelligence through the development and evaluation of specialized Large Language Models (LLMs) PsychoLex is a suite of resources designed to enhance LLMs' proficiency in psychological tasks in both Persian and English. We present the PsychoLexLLaMA model, optimized specifically for psychological applications, demonstrating superior performance compared to general-purpose models.
• Score: 1.3518297878940662
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: This paper explores the intersection of psychology and artificial intelligence through the development and evaluation of specialized Large Language Models (LLMs). We introduce PsychoLex, a suite of resources designed to enhance LLMs' proficiency in psychological tasks in both Persian and English. Key contributions include the PsychoLexQA dataset for instructional content and the PsychoLexEval dataset for rigorous evaluation of LLMs in complex psychological scenarios. Additionally, we present the PsychoLexLLaMA model, optimized specifically for psychological applications, demonstrating superior performance compared to general-purpose models. The findings underscore the potential of tailored LLMs for advancing psychological research and applications, while also highlighting areas for further refinement. This research offers a foundational step towards integrating LLMs into specialized psychological domains, with implications for future advancements in AI-driven psychological practice.

Related papers

• PersLLM: A Personified Training Approach for Large Language Models [66.16513246245401]
  We propose PersLLM, integrating psychology-grounded principles of personality: social practice, consistency, and dynamic development. We incorporate personality traits directly into the model parameters, enhancing the model's resistance to induction, promoting consistency, and supporting the dynamic evolution of personality.
  arXiv  Detail & Related papers  (2024-07-17T08:13:22Z)
• PsycoLLM: Enhancing LLM for Psychological Understanding and Evaluation [27.575675130769437]
  We propose a specialized psychological large language model (LLM), named PsycoLLM, trained on a proposed high-quality psychological dataset. We construct multi-turn dialogues through a three-step pipeline comprising generation, evidence judgment, and refinement. To compare the performance of PsycoLLM with other LLMs, we develop a comprehensive psychological benchmark based on authoritative psychological counseling examinations in China.
  arXiv  Detail & Related papers  (2024-07-08T08:25:56Z)
• Quantifying AI Psychology: A Psychometrics Benchmark for Large Language Models [57.518784855080334]
  Large Language Models (LLMs) have demonstrated exceptional task-solving capabilities, increasingly adopting roles akin to human-like assistants. This paper presents a framework for investigating psychology dimension in LLMs, including psychological identification, assessment dataset curation, and assessment with results validation. We introduce a comprehensive psychometrics benchmark for LLMs that covers six psychological dimensions: personality, values, emotion, theory of mind, motivation, and intelligence.
  arXiv  Detail & Related papers  (2024-06-25T16:09:08Z)
• Optimizing Psychological Counseling with Instruction-Tuned Large Language Models [9.19192059750618]
  This paper explores the application of large language models (LLMs) in psychological counseling. We present a method for instruction tuning LLMs with specialized prompts to enhance their performance in providing empathetic, relevant, and supportive responses.
  arXiv  Detail & Related papers  (2024-06-19T15:13:07Z)
• PsychoGAT: A Novel Psychological Measurement Paradigm through Interactive Fiction Games with LLM Agents [68.50571379012621]
  Psychological measurement is essential for mental health, self-understanding, and personal development. PsychoGAT (Psychological Game AgenTs) achieves statistically significant excellence in psychometric metrics such as reliability, convergent validity, and discriminant validity.
  arXiv  Detail & Related papers  (2024-02-19T18:00:30Z)
• Exploring the Frontiers of LLMs in Psychological Applications: A Comprehensive Review [4.147674289030404]
  Large language models (LLMs) have the potential to simulate aspects of human cognition and behavior. LLMs offer innovative tools for literature review, hypothesis generation, experimental design, experimental subjects, data analysis, academic writing, and peer review in psychology. There are issues like data privacy, the ethical implications of using LLMs in psychological research, and the need for a deeper understanding of these models' limitations.
  arXiv  Detail & Related papers  (2024-01-03T03:01:29Z)
• Evaluating the Efficacy of Interactive Language Therapy Based on LLM for High-Functioning Autistic Adolescent Psychological Counseling [1.1780706927049207]
  This study investigates the efficacy of Large Language Models (LLMs) in interactive language therapy for high-functioning autistic adolescents. LLMs present a novel opportunity to augment traditional psychological counseling methods.
  arXiv  Detail & Related papers  (2023-11-12T07:55:39Z)
• Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View [60.80731090755224]
  This paper probes the collaboration mechanisms among contemporary NLP systems by practical experiments with theoretical insights. We fabricate four unique societies' comprised of LLM agents, where each agent is characterized by a specific trait' (easy-going or overconfident) and engages in collaboration with a distinct thinking pattern' (debate or reflection) Our results further illustrate that LLM agents manifest human-like social behaviors, such as conformity and consensus reaching, mirroring social psychology theories.
  arXiv  Detail & Related papers  (2023-10-03T15:05:52Z)
• Building Emotional Support Chatbots in the Era of LLMs [64.06811786616471]
  We introduce an innovative methodology that synthesizes human insights with the computational prowess of Large Language Models (LLMs) By utilizing the in-context learning potential of ChatGPT, we generate an ExTensible Emotional Support dialogue dataset, named ExTES. Following this, we deploy advanced tuning techniques on the LLaMA model, examining the impact of diverse training strategies, ultimately yielding an LLM meticulously optimized for emotional support interactions.
  arXiv  Detail & Related papers  (2023-08-17T10:49:18Z)
• Machine Psychology [54.287802134327485]
  We argue that a fruitful direction for research is engaging large language models in behavioral experiments inspired by psychology. We highlight theoretical perspectives, experimental paradigms, and computational analysis techniques that this approach brings to the table. It paves the way for a "machine psychology" for generative artificial intelligence (AI) that goes beyond performance benchmarks.
  arXiv  Detail & Related papers  (2023-03-24T13:24:41Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.