Summary of Open Models, Closed Minds? on Agents Capabilities in Mimicking Human Personalities Through Open Large Language Models, by Lucio La Cava et al.
Open Models, Closed Minds? On Agents Capabilities in Mimicking Human Personalities through Open Large Language Models
by Lucio La Cava, Andrea Tagarelli
First submitted to arxiv on: 13 Jan 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Computers and Society (cs.CY); Human-Computer Interaction (cs.HC); Physics and Society (physics.soc-ph)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The researchers study how Large Language Models (LLMs) exhibit human-like behaviors, focusing on open-source models rather than commercially-licensed ones. They create 12 agents based on representative open models and test them using personality assessment tools like Myers-Briggs Type Indicator (MBTI) and Big Five Inventory (BFI). The results show that each agent has distinct human personalities, some can be conditioned to mimic certain traits, but most retain their original characteristics. Combining role and personality conditioning improves the agents’ ability to imitate humans. This work bridges the gap between NLP and human psychology through open LLMs. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large Language Models (LLMs) are getting better at acting like humans. Researchers looked at how these models, which can be used for free, behave like people. They made 12 special “agents” using these models and tested them to see what kind of personalities they had. The results showed that each agent was unique, just like people. Some agents could be trained to act like certain types of people, but most stayed true to themselves. When the researchers tried combining different roles and personalities, it helped the agents behave more like humans. This study helps us understand how language models can learn from human behavior. |
Keywords
» Artificial intelligence » Nlp
