Update README.md

README.md

@@ -1,11 +1,19 @@
-1. Introduction
-   
-We propose \textbf{Pulsar-VLM}, a pulsar candidate identification model built on pretrained multimodal large language models (MLLMs). By integrating visual features from diagnostic subplots with semantic textual descriptions, the model performs geometric morphological reasoning in a manner analogous to expert astronomers.
+# 1. Introduction
 
+We propose **Pulsar-VLM**, a visual reasoning model for pulsar candidate identification, built on pretrained multimodal large language models (MLLMs). The input to Pulsar-VLM includes diagnostic subplots (i.e., frequency-phase plots and DM curves) along with task instructions. By integrating the visual features of the diagnostic subplots with semantic textual descriptions, Pulsar-VLM is able to perform geometric morphological reasoning on the diagnostic plots in a manner analogous to how astronomers interpret them.
 
-2、evaluation dataset
+**Pulsar-VLM maintains high performance across diagnostic plots from commonly used radio telescopes, despite morphological differences, and thus provides substantial benefits to the pulsar research community.**
+
+---
+
+# 2. Evaluation Dataset
+
+![Evaluation Dataset](https://pfst.cf2.poecdn.net/base/image/1a4d214ea08ae2dd1c0d79024f56534673907e70928d48a5c418051c04b8cc9e?w=1220&h=493&pmaid=505863425)
+
+---
+
+# 3. Evaluation Results
 
-3、evaluation results
 | Dataset         | FN  | Recall |
 |-----------------|-----|--------|
 | CRAFTS Dataset  | 3   | 98.8%  |
@@ -18,4 +26,6 @@ We propose \textbf{Pulsar-VLM}, a pulsar candidate identification model built on
 | FAST Dataset    | 1   | 99.7%  |
 | SGAN Dataset    | 577 | 94.5%  |
 
-4、usage
+---
+
+# 4. Usage