3 papers
cs.CL2025
Modeling Layered Consciousness with Multi-Agent Large Language Models
Sang Hun Kim, Jongmin Lee, Dongkyu Park +2
We propose a multi-agent framework for modeling artificial consciousness in large language models (LLMs), grounded in psychoanalytic theory. Our \textbf{Psychodynamic Model} simula…
cs.CL2025
Explain-then-Process: Using Grammar Prompting to Enhance Grammatical Acceptability Judgments
Russell Scheinberg, Ameeta Agrawal, Amber Shore +1
Large language models (LLMs) can explain grammatical rules, yet they often fail to apply those rules when judging sentence acceptability. We present "grammar prompting", an explain…
cs.CL2025
Who Relies More on World Knowledge and Bias for Syntactic Ambiguity Resolution: Humans or LLMs?
So Young Lee, Russell Scheinberg, Amber Shore +1
This study explores how recent large language models (LLMs) navigate relative clause attachment {ambiguity} and use world knowledge biases for disambiguation in six typologically d…