6 citations · 6 across the 3 of their papers we have counts for
4 papers · 1 filter
Aligned Alone, Misaligned Together: Forecasting Adversarial Capture in LLM Agent Populations
Isotta Magistrali, Chen Shani
The unit of AI safety evaluation is still the individual model, yet language-model agents are increasingly deployed in interacting populations that read and write one another's dec…
From Found to Designed: Concepts as a Design Axis for Large Language Models
Chen Shani
Large language models (LLMs) encode rich concept-like information, but represent it implicitly through distributed statistical associations rather than as explicit, structured, com…
Learning Concepts, Not Tokens: Self-Supervised Semantic Alignment for Language Models
Christine Zhang, Dan Jurafsky, Chen Shani
The next-token prediction (NTP) objective trains language models to predict a single token at each step, even though many continuations can express the same meaning. For example, i…
From Tokens to Thoughts: How LLMs and Humans Trade Compression for Meaning
Chen Shani, Liron Soffer, Dan Jurafsky +2
Humans organize knowledge into compact conceptual categories that balance compression with semantic richness. Large Language Models (LLMs) exhibit impressive linguistic abilities,…