Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Paper collection on building and evaluating language model agents via executable language grounding
| Date | Stars |
|---|---|
| 2026-07-31 | 364 |
| 2026-08-01 | 365 |
| 2026-08-06 | 365 |
Today
— stars today
This week
— stars this week
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— stars this month
Momentum
0.0
growth rate 0.00%/day
# XLang Paper Reading
[](https://twitter.com/XLangNLP)
[](https://join.slack.com/t/xlanggroup/shared_invite/zt-20zb8hxas-eKSGJrbzHiPmrADCDX3_rQ)
[](https://discord.gg/4Gnw7eTEZR)
## Introduction
**Exe**cutable **Lang**uage **G**rounding ([XLANG](https://xlang.ai)) focuses on building language model agents that transform (“grounding”) language instructions into code or actions executable in real-world environments, including databases (data agent), web applications (plugins/web agent), and the physical world (robotic agent) etc,. It lies at the heart of language model agents or natural language interfaces that can interact with and learn from these real-world environments to facilitate human interaction with data analysis, web applications, and robotic instruction through conversation. Recent advances in XLang incorporate techniques such as LLM + external tools, code generation, semantic parsing, and dialog or interactive systems.
<div align="center">
<a href="https://xlang.ai">
<img src="https://docs.xlang.ai/assets/images/xlang_overview-89a754ae588aaa568c2294058489ec18.jpg" width="600" />
</a>
</div>
Here we make a paper list for you to keep track of the research in this track. Stay tuned and have fun!
### Paper Group
- [LLM code generation](https://github.com/xlang-ai/xlang-paper-reading/blob/main/llm-code-generation.md)
- [LLM agents (with tool use)](https://github.com/xlang-ai/xlang-paper-reading/blob/main/llm-tool-use.md)
- [LLM web grounding](https://github.com/xlang-ai/xlang-paper-reading/blob/main/llm-web-grounding.md)
- [LLM robotics](https://github.com/xlang-ai/xlang-paper-reading/blob/main/llm-robotics-and-embodied-ai.md)
Excerpt of 2,036 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:9c6b299de6eff56e, topic:large-language-models
matched fp:9c6b299de6eff56e, topic:reinforcement-learning
matched fp:9c6b299de6eff56e, topic:code-generation