Update README.md

README.md

@@ -27,18 +27,18 @@ tags:
 - function-calling
 - tool-calling
 - synthetic
-pretty_name: ToolMesh
+pretty_name: ToolMind
 ---
 
-# ToolMesh: Synthesizing Complex Tool-Use Trajectories via Graph Sampling and Multi-Agent Simulation
+# ToolMind: Synthesizing Complex Tool-Use Trajectories via Graph Sampling and Multi-Agent Simulation
 
-ToolMesh is a large open-source tool-use dataset with reasoning traces, designed to advance reasoning and tool-calling capabilities in agentic LLMs. It comprises over 160k turns synthesized from over 20k tools. By organizing functions as nodes in a graph structure and sampling paths on the graph, we construct complex and high-quality user intents. Then, trajectory is synthesized by a multi-agent way with user and tool are simulted with a LM. Moreover, we perform inference answering and correctness filtering for each round in the trajectory through thinking model, only keeping the correct and valuable turns. Models fine-tuned on ToolMesh achieves promising improvements against baselines on Tau-bench, Tau2-bench and BFCL-v4 agentic.
+ToolMind is a large open-source tool-use dataset with reasoning traces, designed to advance reasoning and tool-calling capabilities in agentic LLMs. It comprises over 160k turns synthesized from over 20k tools. By organizing functions as nodes in a graph structure and sampling paths on the graph, we construct complex and high-quality user intents. Then, trajectory is synthesized by a multi-agent way with user and tool are simulted with a LM. Moreover, we perform inference answering and correctness filtering for each round in the trajectory through thinking model, only keeping the correct and valuable turns. Models fine-tuned on ToolMesh achieves promising improvements against baselines on Tau-bench, Tau2-bench and BFCL-v4 agentic.
 * Technical Report - comming soon
 * HF Dataset - this page is the dataset
 
 # Synthesis pipeline
 
-<img src="./figures/ToolMesh.png" width="700"/>
+<img src="./figures/ToolMind.png" width="700"/>
 
 * Data collection and augmentation 
   * We collect a wide variety of functions from open-source datasets, including [xlam-function-calling-60k](https://huggingface.co/datasets/Salesforce/xlam-function-calling-60k), [glaive-function-calling-v2](https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2), and [ToolACE](https://huggingface.co/datasets/Team-ACE/ToolACE). Each function is expected to have defined inputs and outputs; however, the original definitions are often incomplete — for instance, some functions do not explicitly specify the output parameter types. To unify them within a common representation space, we use powful LMs to complete the descriptions and types of all input and output parameters, and then vectorize them using the embedding model [Conan-embedding-v1](https://huggingface.co/TencentBAC/Conan-embedding-v1).
@@ -62,10 +62,10 @@ ToolMesh is a large open-source tool-use dataset with reasoning traces, designed
 |                          |  Tau2-airline | Tau2-retail | Tau2-telecom | BFCL-v4 | BFCL-v4-agentic |
 |--------------------------|--------------|-------------|--------------|---------|-----------------|
 | qwen3-8b (FC)             |  32.0           | 43.9        | 28.1         | 42.21   | 14.35           |
-| qwen3-8b (FC) w ToolMesh(36w)|  **48.0**           | **59.6**        | **31.6**         | **46.92**   | **20.97**           |
+| qwen3-8b (FC) w ToolMind(36w)|  **48.0**           | **59.6**        | **31.6**         | **46.92**   | **20.97**           |
 |                          |               |             |              |         |                 |
 | qwen3-14b (FC)            |  36.0           | 52.6        | **33.3**         | 45.14   | 16.90           |
-| qwen3-14b (FC) w ToolMesh(36w)|  **56.0**           | **59.6**        | 31.6         | **50.54**   | **26.67**           |
+| qwen3-14b (FC) w ToolMind(36w)|  **56.0**           | **59.6**        | 31.6         | **50.54**   | **26.67**           |
 
 # Ablation Study
 
@@ -74,7 +74,7 @@ ToolMesh is a large open-source tool-use dataset with reasoning traces, designed
 | qwen3-8b (FC)                                    |  32.0           | 43.9        | 28.1         | 42.21   | 14.35           |
 | qwen3-8b (FC) w Augmented Open-Source Data (20w) | <u>44.0</u>           | <u>57.9</u>        | 24.6         | 45.88   | 20.22           |
 | qwen3-8b (FC) w Synthesized Data(16w)            | 42.0           | 43.0        | <u>31.6</u>         | <u>46.87</u>   | **24.37**           |
-| qwen3-8b (FC) w ToolMesh (36w)                   |  **48.0**           | **59.6**        | **31.6**         | **46.92**   | <u>20.97</u>           |
+| qwen3-8b (FC) w ToolMind (36w)                   |  **48.0**           | **59.6**        | **31.6**         | **46.92**   | <u>20.97</u>           |
 
 # Dataset Statistic