Author

Gejin Zhang

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Preprint Sep 2026

Zengram-Lite: An In-Browser Agentic-Memory Framework - Semantic Knowledge, Session Tracking, and Token-Budgeted Context

AI agents increasingly run in the browser, and they need somewhere to keep what they learn. The client-side state of the art, however, is a vector index - nearest-neighbor search over embeddings - with the rest of an agent's memory left to application code: the conversation history is an array in localStorage, context...

Ge-Jin Zhang · 0 citations

#artificial intelligence Preprint Sep 2026

Zeta-Lite: A Concurrent, Branchable In-Browser SQL Database for Agentic Memory

The browser has become a first-class database host: applications increasingly want to store, query, and reason over structured data entirely on the client - for privacy, offline operation, local-first collaboration, and, most recently, as durable memory for in-browser AI agents. One way to get SQL in the browser, compi...

Gejin Zhang · 0 citations

#artificial intelligence Preprint Sep 2026

Relational-Core Graph Analytics Querying graphs at SQL scale, and why the node/edge model is a performance tax, not a truer picture of connected data

This work presents ClickGraph and its Databricks-dialect sibling DeltaGraph, systems that translate Cypher directly onto the native relational schema and execute in place on ClickHouse, Databricks, or in-process on lakehouse files, with no import and no separate cluster.

Ge-Jin Zhang · 0 citations