5 papers
Counterparty Modeling is Not Strategy: The Limits of LLM Negotiators
Romain Cosentino, Sarath Shekkizhar, Adam Earle +1
Negotiation requires more than inferring what the other side wants: it requires using that information to make advantageous offers and counteroffers over multiple turns. We study w…
Beyond the Assistant Turn: User Turn Generation as a Probe of Interaction Awareness in Language Models
Sarath Shekkizhar, Romain Cosentino, Adam Earle
Standard LLM benchmarks evaluate the assistant turn: the model generates a response to an input, a verifier scores correctness, and the analysis ends. This paradigm leaves unmeasur…
Echoing: Identity Failures when LLM Agents Talk to Each Other
Sarath Shekkizhar, Romain Cosentino, Adam Earle +1
As large language model (LLM) based agents interact autonomously with one another, a new class of failures emerges that cannot be predicted from single agent performance: behaviora…
Interaction Theater: A case of LLM Agents Interacting at Scale
Sarath Shekkizhar, Adam Earle
As multi-agent architectures and agent-to-agent protocols proliferate, a fundamental question arises: what actually happens when autonomous LLM agents interact at scale? We study t…
Convergence dynamics of Agent-to-Agent Interactions with Misaligned objectives
Romain Cosentino, Sarath Shekkizhar, Adam Earle
We develop and analyze a theoretical framework for agent-to-agent interactions in a simplified in-context linear regression setting. In our model, each agent is instantiated as a s…