1 citations · 2 across the 4 of their papers we have counts for
5 papers
Beyond Blind Spots: Analytic Hints for Mitigating LLM-Based Evaluation Pitfalls
Ora Nova Fandina, Eitan Farchi, Shmulik Froimovich +4
Large Language Models are increasingly deployed as judges (LaaJ) in code generation pipelines. While attractive for scalability, LaaJs tend to overlook domain specific issues raisi…
Vintage Code, Modern Judges: Meta-Validation in Low Data Regimes
Ora Nova Fandina, Gal Amram, Eitan Farchi +6
Application modernization in legacy languages such as COBOL, PL/I, and REXX faces an acute shortage of resources, both in expert availability and in high-quality human evaluation d…
Automated Validation of LLM-based Evaluators for Software Engineering Artifacts
Ora Nova Fandina, Eitan Farchi, Shmulik Froimovich +4
Automation in software engineering increasingly relies on large language models (LLMs) to generate, review, and assess code artifacts. However, establishing LLMs as reliable evalua…
Exploring Straightforward Conversational Red-Teaming
George Kour, Naama Zwerdling, Marcel Zalmanovici +3
Large language models (LLMs) are increasingly used in business dialogue systems but they pose security and ethical risks. Multi-turn conversations, where context influences the mod…
The Fast Johnson-Lindenstrauss Transform is Even Faster
Ora Nova Fandina, Mikael Møller Høgsgaard, Kasper Green Larsen
The seminal Fast Johnson-Lindenstrauss (Fast JL) transform by Ailon and Chazelle (SICOMP'09) embeds a set of points in -dimensional Euclidean space into optimal $k=O(\vareps…