5 papers
Benchmarking the Benchmarks: Evaluating Benchmarks for Conversational Agents
Noam Koren, Roy Bar-Haim, Abigail Goldsteen
Task-oriented conversational agents are evaluated using curated or automatically generated benchmarks, yet benchmark quality is rarely assessed. Poor benchmarks may contain inconsi…
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…
Debatable Intelligence: Benchmarking LLM Judges via Debate Speech Evaluation
Noy Sternlicht, Ariel Gera, Roy Bar-Haim +2
We introduce Debate Speech Evaluation as a novel and challenging benchmark for assessing LLM judges. Evaluating debate speeches requires a deep understanding of the speech at multi…
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,…
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…