Update README.md
Browse files
README.md
CHANGED
|
@@ -1,3 +1,15 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
# LLM-Agent-Optimization
|
| 2 |
This is the reading list for the survey **"A Survey of LLM-based Agents Optimization" ([Paper Link](https://arxiv.org/abs/2503.12434))**, which systematically explores various optimization techniques for enhancing LLM-based agents. The survey categorizes existing works into parameter-driven optimization, parameter-free optimization, datasets and benchmarks, and real-world applications. We will keep adding papers and improving the list. Any suggestions and PRs are welcome!
|
| 3 |
|
|
|
|
| 1 |
+
---
|
| 2 |
+
title: LLM-based Agent Optimization Paperlist
|
| 3 |
+
emoji: 📐
|
| 4 |
+
colorFrom: indigo
|
| 5 |
+
colorTo: pink
|
| 6 |
+
sdk: gradio
|
| 7 |
+
sdk_version: "4.24.0"
|
| 8 |
+
app_file: app.py
|
| 9 |
+
pinned: false
|
| 10 |
+
---
|
| 11 |
+
|
| 12 |
+
|
| 13 |
# LLM-Agent-Optimization
|
| 14 |
This is the reading list for the survey **"A Survey of LLM-based Agents Optimization" ([Paper Link](https://arxiv.org/abs/2503.12434))**, which systematically explores various optimization techniques for enhancing LLM-based agents. The survey categorizes existing works into parameter-driven optimization, parameter-free optimization, datasets and benchmarks, and real-world applications. We will keep adding papers and improving the list. Any suggestions and PRs are welcome!
|
| 15 |
|