3 papers
cs.AI2026
The Epistemics of Agent Memory: Measuring, and Governing, the Consolidation Decision in Long-Horizon LLM Agents
Sasank Annapureddy, Anjaneya Prasad Thamatani
Long-horizon LLM agents must convert accumulated experience into durable memory, deciding what to keep, compress, abstract into reusable skills and rules, or forget. We report a fo…
cs.AI2026
PRIMUS: Identity, Governance, and Verification for Multi-Agent Federations
Sasank Annapureddy, Anjaneya Prasad Thamatani
Multi-agent federations need governance that answers three questions under adversarial conditions: who participated (identity), did they conform (enforcement), and who decides (aut…
cs.AI2026
StatePlane: A Cognitive State Plane for Long-Horizon AI Systems Under Bounded Context
Sasank Annapureddy, John Mulcahy, Anjaneya Prasad Thamatani
Large language models (LLMs) and small language models (SLMs) operate under strict context window and key-value (KV) cache constraints, fundamentally limiting their ability to reas…