7 papers
System One models Are Not Better Rerankers
Michael Dinzinger, Kanishka Ghosh Dastidar, Michael Granitzer
System One models, or decision models, answer a question about an input with a calibrated probability instead of generated text. Within weeks of the first release, in September 202…
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…
WebFAQ 2.0: A Multilingual QA Dataset with Mined Hard Negatives for Dense Retrieval
Michael Dinzinger, Laura Caspari, Ali Salman +3
We introduce WebFAQ 2.0, a new version of the WebFAQ dataset, containing 198 million FAQ-based natural question-answer pairs across 108 languages. Compared to the previous version,…
CoRECT: A Framework for Evaluating Embedding Compression Techniques at Scale
L. Caspari, M. Dinzinger, K. Ghosh Dastidar +3
Dense retrieval systems have proven to be effective across various benchmarks, but require substantial memory to store large search indices. Recent advances in embedding compressio…
Bridging the Semantic Gap in Virtual Machine Introspection and Forensic Memory Analysis
Christofer Fellicious, Hans P. Reiser, Michael Granitzer
Forensic Memory Analysis (FMA) and Virtual Machine Introspection (VMI) are critical tools for security in a virtualization-based approach. VMI and FMA involves using digital forens…
WebFAQ: A Multilingual Collection of Natural Q&A Datasets for Dense Retrieval
Michael Dinzinger, Laura Caspari, Kanishka Ghosh Dastidar +2
We present WebFAQ, a large-scale collection of open-domain question answering datasets derived from FAQ-style schema.org annotations. In total, the data collection consists of 96 m…
Malware Detection based on API calls
Christofer Fellicious, Manuel Bischof, Kevin Mayer +4
Malware attacks pose a significant threat in today's interconnected digital landscape, causing billions of dollars in damages. Detecting and identifying families as early as possib…