by SAP-samples · AI Tool · ★ 21
KDD 2025 Tutorial: Evaluation & Benchmarking of LLM Agents 📄 Abstract The rise of LLM-based agents has opened new frontiers in AI applications, yet evaluating these agents remains a complex and underdeveloped area. This tutorial provides a systematic survey of the field of LLM agent evaluation, introducing a two-dimensional taxonomy that organizes existing work along: Evaluation objectives (what to evaluate): agent behavior, capabilities, reliability, safety Evaluation process (how to evaluate): interaction modes, datasets and benchmarks, metric computation methods, and tooling In addition,...
| Stars | 21 |
| Forks | 7 |
| Language | Jupyter Notebook |
| Category | AI Tool |
| License | Apache-2.0 |
| Quality Score | 60.2499587208726/100 |
| Last Updated | 2026-06-12 |
| Created | 2025-07-01 |
| Est. Tokens | ~15k |
These tools work well together with llm-agents-eval-tutorial for enhanced workflows:
Explore other popular ai tool tools:
llm-agents-eval-tutorial is Tutorial Materials for the paper "Evaluation & Benchmarking of LLM Agents: A Survey" published in KDD 2025 Conference.. It is categorized as a AI Tool with 21 GitHub stars.
llm-agents-eval-tutorial is primarily written in Jupyter Notebook. It covers topics such as agents, benchmarks, conference.
You can find installation instructions and usage details in the llm-agents-eval-tutorial GitHub repository at github.com/SAP-samples/llm-agents-eval-tutorial. The project has 21 stars and 7 forks, indicating an active community.
llm-agents-eval-tutorial is released under the Apache-2.0 license, making it free to use and modify according to the license terms.