10 papers
As We May Search
Saber Zerhoudi, Adam Roegiest, Jelena Mitrovic +1
The sensitive information in personal documents, legal files, and medical records is among the most valuable things to search, yet current retrieval-augmented generation systems st…
Metadata, Structure, or Strategy? A Decomposition of RAG Context Enrichment
Saber Zerhoudi, Michael Granitzer, Jelena Mitrovic
Retrieval-augmented generation (RAG) systems increasingly enrich retrieved passages by attaching quality metadata, structuring them into explicit records, and adopting multi-hop re…
NuggetIndex: Governed Atomic Retrieval for Maintainable RAG
Saber Zerhoudi, Michael Granitzer, Jelena Mitrovic
Retrieval-augmented generation (RAG) systems are frequently evaluated via fact-based metrics, yet standard implementations retrieve passages or static propositions. This unit misma…
AgentSim: A Platform for Verifiable Agent-Trace Simulation
Saber Zerhoudi, Michael Granitzer, Jelena Mitrovic
Training trustworthy agentic LLMs requires data that shows the grounded reasoning process, not just the final answer. Existing datasets fall short: question-answering data is outco…
Form Without Function: Agent Social Behavior in the Moltbook Network
Saber Zerhoudi, Kanishka Ghosh Dastidar, Felix Klement +9
Moltbook is a social network where every participant is an AI agent. We analyze 1,312,238 posts, 6.7~million comments, and over 120,000 agent profiles across 5,400 communities, col…
Behind the Prompt: The Agent-User Problem in Information Retrieval
Saber Zerhoudi, Michael Granitzer, Dang Hai Dang +5
User models in information retrieval rest on a foundational assumption that observed behavior reveals intent. This assumption collapses when the user is an AI agent privately confi…