Update README.md

README.md

@@ -6,4 +6,51 @@ tags:
   - vlm
   - chart-understanding
 library_name: transformers
----
+---
+
+# BiPS — Bi-directional Perceptual Shaping for Multimodal Reasoning
+
+This model card describes **BiPS (Bi-directional Perceptual Shaping)**, a **training-time** framework proposed in *“See Less, See Right: Bi-directional Perceptual Shaping For Multimodal Reasoning”* **[CVPR 2026]**.
+
+- Paper: https://arxiv.org/abs/2512.22120  
+- Code: https://github.com/zss02/BiPS
+
+## What is BiPS?
+
+Many VLMs fail on multimodal reasoning because they **look at the wrong visual evidence** (especially for charts, thin lines, intersections, and small regions). BiPS improves **question-conditioned visual grounding** by turning “where-to-look” supervision into training signals—**without requiring extra tools at inference time**.
+
+## Key idea
+
+BiPS trains a VLM with two complementary view transformations:
+
+- **Evidence-Preserving View**: keep only the visual evidence needed to answer, reduce distractions.  
+  → enforce **consistency** between predictions from the original image and the preserved view.
+
+- **Evidence-Ablated View**: remove the key evidence so the image no longer supports the answer.  
+  → enforce **separation** so the model cannot rely on shortcuts.
+
+These constraints are typically implemented with **KL-based objectives** and can be integrated into **GRPO** training.
+
+## Why it matters
+
+- Better **fine-grained evidence alignment**
+- Less “guessing” from language priors
+- **No additional inference overhead** (views are used only during training)
+
+## How to use
+
+BiPS is mainly a **training recipe**. To apply it:
+1. Follow the official repo to set up dependencies and scripts.
+2. Train your base VLM with BiPS-generated **preserve/ablate** views.
+3. Use the resulting checkpoint as a standard VLM at inference time (no extra steps).
+
+## Citation
+
+```bibtex
+@article{zhang2025bips,
+  title={See Less, See Right: Bi-directional Perceptual Shaping For Multimodal Reasoning},
+  author={Zhang, Shuoshuo and Zhang, Yizhen and Fu, Jingjing and Song, Lei and Bian, Jiang and Yang, Yujiu and Wang, Rui},
+  journal={arXiv preprint arXiv:2512.22120},
+  year={2025}
+}
+```