Initial submission

README.md

@@ -1,3 +1,115 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+task_categories:
+- question-answering
+- feature-extraction
+language:
+- en
+tags:
+- eda
+- analog
+- vlm
+pretty_name: Analog Layouts Dataset for Vision Language Models (VLMs)
+---
+
+# A VLM Framework to Optimize the Analysis of Analog Circuit Layouts
+
+***ICML 2026 Submission - Under Review***
+
+This repository contains the dataset presented in the paper *"A VLM Framework to Optimize the Analysis of Analog Circuit Layouts"*, along with the code for training and evaluating Visual Language Models (VLMs) on analog circuit layouts analysis tasks.
+
+The project addresses the challenge of interpreting technical diagrams by benchmarking VLMs on tasks ranging from single device identification to component counting in complex mixed circuits.
+
+## Dataset Overview
+
+The dataset comprises over **30,000 circuits** and **77,000+ Question-Answer pairs**, organized into a comprehensive benchmark suite.
+
+### Circuit Categories
+- **Single Devices** (19,997 images): PMOS, NMOS, Capacitors, Resistors.
+- **Base Circuits** (5,894 images): Ahuja OTA, Gate Driver, HPF, LDO, LPF, Miller OTA.
+- **Mixed Circuits** (4,140 images): Complex combinations of base circuits.
+
+### Benchmark Tasks
+The dataset defines 5 core tasks for evaluation:
+| Task | Description | Size |
+|------|-------------|------|
+| **Task A** | Single device identification | 19,997 samples |
+| **Task B** | Base circuit identification | 5,894 samples |
+| **Task C** | Component counting (base circuits) | 27,475 samples |
+| **Task D** | Component counting (mixed circuits) | 19,848 samples |
+| **Task E** | Base circuit identification in mixed circuits | 4,140 samples |
+
+*For detailed statistics, please refer to [DATASET_STATISTICS.md](DATASET_STATISTICS.md).*
+
+## Repository Structure
+Once `code.zip` and `dataset.zip` have been unzipped, the structure is as follows:
+```
+.
+├── code/               # Source code for fine-tuning and inference
+├── base_circuits/      # Base circuit datasets and templates
+├── mixed_circuits/     # Mixed circuit datasets
+├── single_devices/     # Single device datasets
+├── tasks/              # Task definitions and data splits
+└── DATASET_STATISTICS.md
+```
+
+## Getting Started
+
+### Prerequisites
+All execution scripts are located in the `code/` directory.
+
+```bash
+cd code
+pip install -r requirements.txt
+```
+
+### Fine-Tuning
+The repository provides a sequential fine-tuning launcher to handle dataset ablations and multiple tasks.
+
+**Basic Usage:**
+```bash
+# Dry-run to view planned training jobs
+python VLM_finetune/run_ablation_sequential_ft.py --dry_run
+
+# Train Task A (Single device identification) with 100% of dataset
+python VLM_finetune/run_ablation_sequential_ft.py --task a1 --perc 100
+```
+
+**Advanced Usage:**
+Train multiple tasks with specific data percentages:
+```bash
+python VLM_finetune/run_ablation_sequential_ft.py --tasks a1,b1,c1 --percs 25,50,75,100
+```
+
+### Evaluation
+The inference pipeline supports evaluating both base models and fine-tuned LoRA adapters.
+
+**Batch Evaluation (Ablation Study):**
+Evaluate many adapters across different tasks and splits:
+```bash
+python VLM_inference/run_ft_eval_ablation.py \
+    --splits-root /path/to/dataset/ablation_splits \
+    --adapter-root /path/to/outputs/finetune_lora \
+    --cache-dir /path/to/cache
+```
+
+**Result Reorganization:**
+Map raw evaluation results from training tasks (A1/B1/C1) to the final benchmark tasks (A-E) and compute aggregated metrics:
+```bash
+python reorganize_results.py \
+    --input-root /path/to/raw_results \
+    --output-root /path/to/final_results
+```
+
+**Single Task Evaluation:**
+Run inference on a single task/circuit:
+```bash
+# Evaluate Task A (Task A1)
+python VLM_inference/test_base_models/run_ft_eval_update.py --task a1 --num-samples 200
+
+# Evaluate with a specific adapter
+python VLM_inference/test_base_models/run_ft_eval_update.py \
+    --task a1 \
+    --num-samples 200 \
+    --adapter /path/to/adapter/checkpoint
+```