activity
20232026
most citedPredicting Question-Answering Performance of Large Language Models through Semantic Consistency

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Near-Miss: Latent Policy Failure Detection in Agentic Workflows

Ella Rabinovich, David Boaz, Naama Zwerdling +1

Agentic systems for business process automation often require compliance with policies governing conditional updates to the system state. Evaluation of policy adherence in LLM-base…

cs.CL2025

Towards Enforcing Company Policy Adherence in Agentic Workflows

Naama Zwerdling, David Boaz, Ella Rabinovich +3

Large Language Model (LLM) agents hold promise for a flexible and scalable alternative to traditional business process automation, but struggle to reliably follow complex company p…

cs.CL2025

On the Robustness of Agentic Function Calling

Ella Rabinovich, Ateret Anaby-Tavor

Large Language Models (LLMs) are increasingly acting as autonomous agents, with function calling (FC) capabilities enabling them to invoke specific tools for tasks. While prior res…

cs.CL2024

A Novel Metric for Measuring the Robustness of Large Language Models in Non-adversarial Scenarios

Samuel Ackerman, Ella Rabinovich, Eitan Farchi +1

We evaluate the robustness of several large language models on multiple datasets. Robustness here refers to the relative insensitivity of the model's answers to meaning-preserving…

cs.CL2023★ 1 cited

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…