activity
20202026
most citedGeneral Agent Evaluation

2 citations · 3 across the 7 of their papers we have counts for

collaborators

10 papers

cs.CL2026

Agentic CLEAR: Automating Multi-Level Evaluation of LLM Agents

Asaf Yehudai, Lilach Eden, Michal Shmueli-Scheuer

Agentic systems are becoming more capable: agents define strategies, take actions, and interact with different environments. This autonomy poses serious challenges for overseeing a…

cs.AI2026★ 2 cited

General Agent Evaluation

Elron Bandel, Asaf Yehudai, Lilach Eden +12

General-purpose agents perform tasks in unfamiliar environments without domain-specific manual customization. Yet no study has systematically measured how agent architecture shapes…

cs.CL2025

CLEAR: Error Analysis via LLM-as-a-Judge Made Easy

Asaf Yehudai, Lilach Eden, Yotam Perlitz +2

The evaluation of Large Language Models (LLMs) increasingly relies on other LLMs acting as judges. However, current evaluation paradigms typically yield a single score or ranking,…

cs.AI2025

Survey on Evaluation of LLM-based Agents

Asaf Yehudai, Lilach Eden, Alan Li +5

LLM-based agents represent a paradigm shift in AI, enabling autonomous systems to plan, reason, and use tools while interacting with dynamic environments. This paper provides the f…

cs.CL2024

JuStRank: Benchmarking LLM Judges for System Ranking

Ariel Gera, Odellia Boni, Yotam Perlitz +3

Given the rapid progress of generative AI, there is a pressing need to systematically compare and choose between the numerous models and configurations available. The scale and ver…

cs.CL2023

CHAMP: Efficient Annotation and Consolidation of Cluster Hierarchies

Arie Cattan, Tom Hope, Doug Downey +4

Various NLP tasks require a complex hierarchical structure over nodes, where each node is a cluster of items. Examples include generating entailment graphs, hierarchical cross-docu…

cs.CL2023★ 1 cited

From Key Points to Key Point Hierarchy: Structured and Expressive Opinion Summarization

Arie Cattan, Lilach Eden, Yoav Kantor +1

Key Point Analysis (KPA) has been recently proposed for deriving fine-grained insights from collections of textual comments. KPA extracts the main points in the data as a list of c…

cs.CL2021

Every Bite Is an Experience: Key Point Analysis of Business Reviews

Roy Bar-Haim, Lilach Eden, Yoav Kantor +2

Previous work on review summarization focused on measuring the sentiment toward the main aspects of the reviewed product or business, or on creating a textual summary. These approa…

cs.CL2020

Quantitative Argument Summarization and Beyond: Cross-Domain Key Point Analysis

Roy Bar-Haim, Yoav Kantor, Lilach Eden +3

When summarizing a collection of views, arguments or opinions on some topic, it is often desirable not only to extract the most salient points, but also to quantify their prevalenc…

cs.CL2020

From Arguments to Key Points: Towards Automatic Argument Summarization

Roy Bar-Haim, Lilach Eden, Roni Friedman +3

Generating a concise summary from a large collection of arguments on a given topic is an intriguing yet understudied problem. We propose to represent such summaries as a small set…