4 papers
Reasoning as Pattern Matching: Shared Mechanisms in Human and LLM Everyday Reasoning
Zach Studdiford, Gary Lupyan
When large language models (LLMs) fail to generalize or make haphazard errors in reasoning, it is often taken as evidence that LLMs are not truly reasoning, but rather performing a…
Uncovering the Computational Ingredients of Human-Like Representations in LLMs
Zach Studdiford, Timothy T. Rogers, Kushin Mukherjee +1
The ability to translate diverse patterns of inputs into structured patterns of behavior has been thought to rest on both humans' and machines' ability to learn robust representati…
Evaluating Steering Techniques using Human Similarity Judgments
Zach Studdiford, Timothy T. Rogers, Siddharth Suresh +1
Current evaluations of Large Language Model (LLM) steering techniques focus on task-specific performance, overlooking how well steered representations align with human cognition. U…
Beyond Demographics: Aligning Role-playing LLM-based Agents Using Human Belief Networks
Yun-Shiuan Chuang, Krirk Nirunwiroj, Zach Studdiford +6
Creating human-like large language model (LLM) agents is crucial for faithful social simulation. Having LLMs role-play based on demographic information sometimes improves human lik…