8 citations · 31 across the 29 of their papers we have counts for
4 papers · 1 filter
Unveiling Safety Vulnerabilities of Large Language Models
George Kour, Marcel Zalmanovici, Naama Zwerdling +5
As large language models become more prevalent, their possible harmful or inappropriate responses are a cause for concern. This paper introduces a unique dataset containing adversa…
Predicting Question-Answering Performance of Large Language Models through Semantic Consistency
Ella Rabinovich, Samuel Ackerman, Orna Raz +2
Semantic consistency of a language model is broadly defined as the model's ability to produce semantically-equivalent outputs, given semantically-equivalent inputs. We address the…
Characterizing how 'distributional' NLP corpora distance metrics are
Samuel Ackerman, George Kour, Eitan Farchi
A corpus of vector-embedded text documents has some empirical distribution. Given two corpora, we want to calculate a single metric of distance (e.g., Mauve, Frechet Inception) bet…
Data Drift Monitoring for Log Anomaly Detection Pipelines
Dipak Wani, Samuel Ackerman, Eitan Farchi +3
Logs enable the monitoring of infrastructure status and the performance of associated applications. Logs are also invaluable for diagnosing the root causes of any problems that may…