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README.md

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 The Knowledge Engineering Group (**[KEG](https://twitter.com/thukeg)**) & Data Mining ([THUDM](https://github.com/THUDM)) at Tsinghua University. 
 
-We build **LLMs** and related training & inference techniques: 
+We build **LLMs**, develop LLMs as **Agents** as well as develop related LLM training & inference techniques: 
 
-* **[ChatGLM](https://github.com/THUDM/ChatGLM3)**, 
+* **[ChatGLM](https://github.com/THUDM/GLM-4)**, 
   **[CodeGeeX](https://github.com/THUDM/CodeGeeX2)**,
-  **[CogVLM (VisualGLM)](https://github.com/THUDM/CogVLM)**,
+  **[CogVLM (VisualGLM)](https://github.com/THUDM/CogVLM2)**,
   **[WebGLM](https://github.com/THUDM/WebGLM)**,
   **[GLM-130B](https://github.com/THUDM/GLM-130B)**,
   **[CogView](https://github.com/THUDM/CogView)**,
-  **[CogVideo](https://github.com/THUDM/CogVideo)**. 
-
-  **[CogAgent](https://github.com/THUDM/CogVLM)**: A Visual Language Model for GUI Agents
-  **[AgentTuning](https://github.com/THUDM/AgentTuning)**: Enabling Generalized Agent Abilities for LLMs
-  **[APAR](https://arxiv.org/abs/2401.06761)**: LLMs Can Do Auto-Parallel Auto-Regressive Decoding
+  **[CogVideo](https://github.com/THUDM/CogVideo)**,
+* **[CogAgent](https://github.com/THUDM/CogVLM)**,
+  **[AutoWebGLM](https://github.com/THUDM/AutoWebGLM)**,
+  **[AgentTuning](https://github.com/THUDM/AgentTuning)**, 
+  **[APAR](https://arxiv.org/abs/2401.06761)**. 
 
 We also work on **LLM evaluations**: 
 * **[AgentBench](https://github.com/THUDM/AgentBench)**,
   **[AlignBench](https://github.com/THUDM/AlignBench)**,
-  **[LongBench](https://github.com/THUDM/LongBench)**.
+  **[LongBench](https://github.com/THUDM/LongBench)**,
+  **[NaturalCodeBench](https://github.com/THUDM/NaturalCodeBench)**. 
  
 
 We also **pre-train graph neural networks**: