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20242026
most citedAgents of Chaos

6 citations · 6 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.CL2026

Emergence of Hierarchical Emotion Organization in Large Language Models

Maya Okawa, Bo Zhao, Eric J. Bigelow +4

As large language models (LLMs) increasingly power conversational agents, understanding how they model users' emotional states is critical for ethical deployment. Inspired by emoti…

cs.CL2026

Cognitive models can reveal interpretable value trade-offs in language models

Sonia K. Murthy, Rosie Zhao, Jennifer Hu +4

Value trade-offs are an integral part of human decision-making and language use, however, current tools for interpreting such dynamic and multi-faceted notions of values in languag…

cs.CL2025

One fish, two fish, but not the whole sea: Alignment reduces language models' conceptual diversity

Sonia K. Murthy, Tomer Ullman, Jennifer Hu

Researchers in social science and psychology have recently proposed using large language models (LLMs) as replacements for humans in behavioral research. In addition to arguments a…

cs.CL2025

Shades of Zero: Distinguishing Impossibility from Inconceivability

Jennifer Hu, Felix Sosa, Tomer Ullman

Some things are impossible, but some things may be even more impossible than impossible. Levitating a feather using one's mind is impossible in our world, but fits into our intuiti…

cs.CL2024

Forking Paths in Neural Text Generation

Eric Bigelow, Ari Holtzman, Hidenori Tanaka +1

Estimating uncertainty in Large Language Models (LLMs) is important for properly evaluating LLMs, and ensuring safety for users. However, prior approaches to uncertainty estimation…