24 citations · 28 across the 14 of their papers we have counts for
10 papers · 1 filter
Faithful Query Resolution for Conversational Search
Saber Zerhoudi, Ivica Kostric, Jelena Mitrovic
Conversational query rewriting makes context-dependent requests explicit for retrieval, but additional context can introduce an information need the user did not express. This rais…
The Fellowship of the Query: Learning Retrieval Actions
Mohammed Al-Maamari, Saber Zerhoudi, Michael Granitzer +1
Retrieval-augmented question answering requires control decisions about when to decompose a question, search, reformulate, extract evidence, synthesize facts, verify progress, and…
When Is Complex Chunking Worth It? A Multi-Objective Evaluation of Chunking Methods at Scale
Laura Caspari, Kanishka Ghosh Dastidar, Michael Dinzinger +2
Dense retrieval is commonly evaluated on benchmarks that represent each document with a single embedding, even though real-world retrieval systems often index long documents that r…
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…
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…
Beyond Benchmarks: Evaluating Embedding Model Similarity for Retrieval Augmented Generation Systems
Laura Caspari, Kanishka Ghosh Dastidar, Saber Zerhoudi +2
The choice of embedding model is a crucial step in the design of Retrieval Augmented Generation (RAG) systems. Given the sheer volume of available options, identifying clusters of…
A Benchmark of PDF Information Extraction Tools using a Multi-Task and Multi-Domain Evaluation Framework for Academic Documents
Norman Meuschke, Apurva Jagdale, Timo Spinde +2
Extracting information from academic PDF documents is crucial for numerous indexing, retrieval, and analysis use cases. Choosing the best tool to extract specific content elements…