7 papers
Toward Personal Intelligence Through Cooperative Observation
Yashar Talebirad, Osman Jime, Ali Parsaee +3
A personal AI system needs a model of the user's goals, constraints, and ongoing commitments to plan and act on their behalf, and the quality of that model is bounded by what the s…
Memory Is Communication: The Frontier Between Remembering and Signaling
Yashar Talebirad, Eden Redman, Ali Parsaee +1
A bounded agent may obtain information for a decision from its own past, from peers, or from both sources. Retaining task-relevant history can reduce later communication, while a p…
From Signals to Structure: How Memory Architecture Drives Language Emergence in LLM Agents
Yashar Talebirad, Eden Redman, Ali Parsaee +1
How do two agents invent a shared language from scratch? In a Lewis signaling game, a sender and receiver must coordinate on a code using only their interaction history. We study f…
Toward a Theory of Hierarchical Memory for Language Agents
Yashar Talebirad, Ali Parsaee, Csongor Y. Szepesvari +2
Many recent long-context and agentic systems address context-length limitations by adding hierarchical memory: they extract atomic units from raw data, build multi-level representa…
LoopBench: Discovering Emergent Symmetry Breaking Strategies with LLM Swarms
Ali Parsaee, Yashar Talebirad, Csongor Szepesvári +2
Large Language Models (LLMs) are increasingly being utilized as autonomous agents, yet their ability to coordinate in distributed systems remains poorly understood. We introduce \t…
Budget-constrained Active Learning to Effectively De-censor Survival Data
Ali Parsaee, Bei Jiang, Zachary Friggstad +1
Standard supervised learners attempt to learn a model from a labeled dataset. Given a small set of labeled instances, and a pool of unlabeled instances, a budgeted learner can use…