32 citations · 39 across the 23 of their papers we have counts for
15 papers · 1 filter
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…
CRISP: Complex Reasoning with Interpretable Step-based Plans
Matan Vetzler, Koren Lazar, Guy Uziel +3
Recent advancements in large language models (LLMs) underscore the need for stronger reasoning capabilities to solve complex problems effectively. While Chain-of-Thought (CoT) reas…
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…
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…
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…
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…
SpeCrawler: Generating OpenAPI Specifications from API Documentation Using Large Language Models
Koren Lazar, Matan Vetzler, Guy Uziel +4
In the digital era, the widespread use of APIs is evident. However, scalable utilization of APIs poses a challenge due to structure divergence observed in online API documentation.…
What's the Plan? Evaluating and Developing Planning-Aware Techniques for Language Models
Eran Hirsch, Guy Uziel, Ateret Anaby-Tavor
Planning is a fundamental task in artificial intelligence that involves finding a sequence of actions that achieve a specified goal in a given environment. Large language models (L…
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…
Measuring the Measuring Tools: An Automatic Evaluation of Semantic Metrics for Text Corpora
George Kour, Samuel Ackerman, Orna Raz +3
The ability to compare the semantic similarity between text corpora is important in a variety of natural language processing applications. However, standard methods for evaluating…
Understanding the Properties of Generated Corpora
Naama Zwerdling, Segev Shlomov, Esther Goldbraich +6
Models for text generation have become focal for many research tasks and especially for the generation of sentence corpora. However, understanding the properties of an automaticall…
Gaining Insights into Unrecognized User Utterances in Task-Oriented Dialog Systems
Ella Rabinovich, Matan Vetzler, David Boaz +3
The rapidly growing market demand for automatic dialogue agents capable of goal-oriented behavior has caused many tech-industry leaders to invest considerable efforts into task-ori…
Improved Goal Oriented Dialogue via Utterance Generation and Look Ahead
Eyal Ben-David, Boaz Carmeli, Ateret Anaby-Tavor
Goal oriented dialogue systems have become a prominent customer-care interaction channel for most businesses. However, not all interactions are smooth, and customer intent misunder…
We've had this conversation before: A Novel Approach to Measuring Dialog Similarity
Ofer Lavi, Ella Rabinovich, Segev Shlomov +3
Dialog is a core building block of human natural language interactions. It contains multi-party utterances used to convey information from one party to another in a dynamic and evo…
Not Enough Data? Deep Learning to the Rescue!
Ateret Anaby-Tavor, Boaz Carmeli, Esther Goldbraich +5
Based on recent advances in natural language modeling and those in text generation capabilities, we propose a novel data augmentation method for text classification tasks. We use a…