Update README.md

README.md

@@ -13,8 +13,34 @@
 
 # Introduction
 
-
-## Key Features
+We are delighted to release Infinity-Parser2-2B, our latest state-of-the-art document understanding model. Compared to our prior model, Infinity-Parser-7B, we have deeply optimized our data engine and multi-task reinforcement learning. We have successfully condensed robust multi-modal parsing capabilities into a highly efficient 2B-parameter model, offering massive speedups and brand-new zero-shot capabilities for real-world business scenarios.
+
+## 🌟 Key Features
+
+### 📚 Upgraded Data Engine
+- **Massive & Diverse Data:** Added **1M+ full-text samples** across 9 document types (academic, financial, books, etc.).
+- **Targeted Enrichment:** Injected 170K synthetic financial tables, 900K formulas, and 5K negative samples to mitigate hallucinations.
+- **Adaptive Sampling:** Dynamically adjusts data distribution based on task importance and dataset size for balanced learning.
+
+### 🧠 Multi-Task Reinforcement Learning
+- **Verifiable Reward System:** Designed a novel reward mechanism to support Joint Reinforcement Learning (RL).
+- **Unified Optimization:** Simultaneously co-optimizes multiple tasks, ranging from full-text and table parsing to layout analysis and Document VQA.
+
+### 📈 Breakthrough Parsing Performance
+Despite its compact 2B size, it significantly outperforms our previous 7B model:
+- **Domain SOTA:** Achieves SOTA on financial benchmarks (`FinDocBench`, `FinTabBench`), surpassing frontier models like DeepSeek-OCR2, GLM-OCR, and PaddleOCR-VL-v1.5.
+- **Public Benchmarks:** Achieves SOTA on `olmOCR-Bench` and `PubTabNet`, with highly competitive results on `OmniDocBench-v1.5` and `UniMERNet`.
+- **General Multimodal:** Scores **66.06** on average across 7 benchmarks (e.g., MathVista, MMMU), beating the Qwen3-VL-2B base (+3.2pt).
+
+### 🚀 Massive Inference Acceleration (3.68x Faster)
+- **Optimized Architecture:** Transitioned to the highly efficient **Qwen3-VL-2B** base model.
+- **Blazing Fast:** Inference throughput surged by **3.68x** (from 441 to **1,624 tokens/sec**), slashing latency and deployment costs without accuracy drop.
+
+### ✨ Expanded Capabilities (Zero-to-One Additions)
+Unlocked entirely new skills in this release:
+- **Chart Parsing:** Scores 79.91 on `Chart2Table`.
+- **Chemical Structures:** Scores 68.05 on our new `ChemDraw-198` and 52.78 on `CoSyn-Chemical`.
+- **Layout Analysis:** Achieves 64.92 on `DocLayNet` and 73.16 on `OmniDocBench-v1.5-layout`, matching dedicated layout models like DocLayout-YOLO.
 
 # Architecture