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README.md

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+---
+license: mit
+library_name: icmil
+tags:
+  - multiple-instance-learning
+  - in-context-learning
+  - prior-data-fitted-network
+  - tabular
+datasets:
+  - bifold-pathomics/ICMIL
+pipeline_tag: tabular-classification
+---
+
+# ICMIL — In-Context Multiple Instance Learning
+
+📄 [Paper (arXiv:2606.06458)](https://arxiv.org/abs/2606.06458) · 💻 [Code](https://github.com/injurise/ICMIL) · 🤗 [Datasets](https://huggingface.co/datasets/bifold-pathomics/ICMIL)
+
+ICMIL is an in-context learner for bag-structured data: pretrained on synthetic MIL
+tasks, it labels the bags of a new task from a handful of labelled bags in a single
+forward pass, with no gradient updates, fine-tuning or hyper-parameter search.
+
+This repository holds the three trained model seeds behind the paper's
+**ICMIL (Ours)** results. The same checkpoints are committed in the code repository
+under [`checkpoints/`](https://github.com/injurise/ICMIL/tree/main/checkpoints).
+
+## Files
+
+| File | Seed name |
+|---|---|
+| `icmil-c5trd795.pt` | `c5trd795` |
+| `icmil-ggwsqibd.pt` | `ggwsqibd` |
+| `icmil-k337zhz1.pt` | `k337zhz1` |
+
+Seed names are opaque run labels. Each `.pt` holds
+`{model_state_dict, epoch, ...provenance}`. The reported ICMIL row is the
+**mean ± cross-seed SEM** over the three seeds.
+
+We also provide three 50-feature seeds —
+`icmil-50dim-ldsebntm.pt`, `icmil-50dim-sjik4hzb.pt`, `icmil-50dim-zeqy97nm.pt`.
+No paper results are based on them.
+
+## Usage
+
+```python
+from icmil import load_icmil  # pip install -e . from https://github.com/injurise/ICMIL
+
+model = load_icmil(seed="c5trd795", device="cuda")
+# X_train: (1, n_ctx_bags, bag_size, n_features), y_train: (1, n_ctx_bags)
+# X_test:  (1, n_query_bags, bag_size, n_features)
+logits = model(X_train, y_train, X_test)   # (1, n_query_bags, n_classes)
+```
+
+`load_icmil` reads `checkpoints/` in the repo by default; point it elsewhere with
+`load_icmil(source="/path/to/ckpts", seed=...)` or `ICMIL_CKPT_DIR`. Reproduce the
+full benchmark table with `python -m icmil.reproduce`.
+
+## Citation
+
+```bibtex
+@article{mollers2026incontext,
+  title   = {In-Context Multiple Instance Learning},
+  author  = {M\"ollers, Alexander and Sextro, Marvin and Hense, Julius and Dernbach, Gabriel and M\"uller, Klaus-Robert},
+  journal = {arXiv preprint arXiv:2606.06458},
+  year    = {2026}
+}
+```

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