3 papers
cs.LG2026
Dynamic Budget Allocation for LLM Evaluation under Hard Resource Constraints
Shai Feldman, Yaniv Romano
We evaluate large language models (LLMs) in multi-turn interactions through their time-to-event: the number of interaction steps required to produce an event of interest, such as a…
cs.LG2026
How Many Iterations to Jailbreak? Dynamic Budget Allocation for Multi-Turn LLM Evaluation
Shai Feldman, Yaniv Romano
Evaluating and predicting the performance of large language models (LLMs) in multi-turn conversational settings is critical yet computationally expensive; key events---e.g., jailbr…
cs.LG2025
Calibrated Predictive Lower Bounds on Time-to-Unsafe-Sampling in LLMs
Hen Davidov, Shai Feldman, Gilad Freidkin +1
We introduce time-to-unsafe-sampling, a novel safety measure for generative models, defined as the number of generations required by a large language model (LLM) to trigger an unsa…