diff --git a/.gitattributes b/.gitattributes
index af1894c7bde37ac570b59b797b1ed39b82d26152..77c5fded1ed32f0d6aa86df56194a3999856c6bb 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -33,3 +33,26 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 models/replogle_k562/model.pt filter=lfs diff=lfs merge=lfs -text
+models/ablations/norman_perturbation/comp_map/model.pt filter=lfs diff=lfs merge=lfs -text
+models/ablations/norman_perturbation/comp_map_semi/model.pt filter=lfs diff=lfs merge=lfs -text
+models/ablations/norman_perturbation/comp_map_tan/model.pt filter=lfs diff=lfs merge=lfs -text
+models/ablations/norman_perturbation/default/model.pt filter=lfs diff=lfs merge=lfs -text
+models/ablations/norman_perturbation/frac_0.1/model.pt filter=lfs diff=lfs merge=lfs -text
+models/ablations/norman_perturbation/frac_0.25/model.pt filter=lfs diff=lfs merge=lfs -text
+models/ablations/norman_perturbation/frac_0.5/model.pt filter=lfs diff=lfs merge=lfs -text
+models/ablations/norman_perturbation/frac_0.75/model.pt filter=lfs diff=lfs merge=lfs -text
+models/ablations/norman_perturbation/match_batch_celltype/model.pt filter=lfs diff=lfs merge=lfs -text
+models/ablations/norman_perturbation/match_celltype/model.pt filter=lfs diff=lfs merge=lfs -text
+models/ablations/norman_perturbation/match_nearest/model.pt filter=lfs diff=lfs merge=lfs -text
+models/ablations/norman_perturbation/match_ot/model.pt filter=lfs diff=lfs merge=lfs -text
+models/ablations/norman_perturbation/match_random/model.pt filter=lfs diff=lfs merge=lfs -text
+models/ablations/norman_perturbation/rep_gene_only/model.pt filter=lfs diff=lfs merge=lfs -text
+models/ablations/norman_perturbation/rep_gene_pathway_op/model.pt filter=lfs diff=lfs merge=lfs -text
+models/ablations/norman_perturbation/rep_op_only/model.pt filter=lfs diff=lfs merge=lfs -text
+models/ablations/norman_perturbation/rep_random_id/model.pt filter=lfs diff=lfs merge=lfs -text
+models/norman/cell/model.pt filter=lfs diff=lfs merge=lfs -text
+models/norman/combination/model.pt filter=lfs diff=lfs merge=lfs -text
+models/norman/perturbation/model.pt filter=lfs diff=lfs merge=lfs -text
+models/replogle_k562/cell/model.pt filter=lfs diff=lfs merge=lfs -text
+models/replogle_k562/gene/model.pt filter=lfs diff=lfs merge=lfs -text
+models/replogle_k562/perturbation/model.pt filter=lfs diff=lfs merge=lfs -text
diff --git a/README.md b/README.md
index 231b28eac09350b36b58e203dfc9e01d0eea3227..89e882a32b430724f65da30e29f89f42d9864cf5 100644
--- a/README.md
+++ b/README.md
@@ -64,10 +64,13 @@ conda run -n pivot_gears python scripts/gears_ranking.py
 
 ## Models
 
-Trained PIVOT checkpoints live under `models/`:
+Every model behind the paper is checkpointed under `models/`, and `scripts/train_all.py`
+retrains them from scratch with the same configs and seed, so the numbers reproduce.
 
-- `models/norman/` - trained on Norman 2019 (CRISPRa K562)
-- `models/replogle_k562/` - trained on Replogle 2022 (CRISPRi K562)
+- `models/norman/{cell,perturbation,combination}/` - Norman 2019 (CRISPRa K562), one per split
+- `models/replogle_k562/{cell,perturbation,gene}/` - Replogle 2022 (CRISPRi K562), one per split
+- `models/ablations/norman_perturbation/` - the ablation variants (loss components, perturbation
+  representation, training-data fraction, control-matching strategy), each a separate folder
 
 each folder has `model.pt` (a plain torch state dict), `config.json` (the training config),
 and `train_info.json` (history + run info). loading needs the matching preprocessed dataset,
@@ -78,13 +81,19 @@ import json, torch
 from src.data.perturb_data import load_dataset
 from src.training.train import TrainConfig, make_model
 
-cfg = TrainConfig(**json.load(open("models/norman/config.json")))
+cfg = TrainConfig(**json.load(open("models/norman/perturbation/config.json")))
 data = load_dataset(cfg.dataset)
 model = make_model(data, cfg, device="cpu")
-model.load_state_dict(torch.load("models/norman/model.pt", map_location="cpu"))
+model.load_state_dict(torch.load("models/norman/perturbation/model.pt", map_location="cpu"))
 model.eval()
 ```
 
+To retrain everything:
+
+```bash
+python scripts/train_all.py
+```
+
 ## License
 
 MIT, Bryan Cheng 2026. See `LICENSE`.
diff --git a/models/ablations/norman_perturbation/comp_map/config.json b/models/ablations/norman_perturbation/comp_map/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..6fa89ca30768599ce88bf517a5c142595455a72b
--- /dev/null
+++ b/models/ablations/norman_perturbation/comp_map/config.json
@@ -0,0 +1,28 @@
+{
+  "dataset": "norman",
+  "embedding": "pca",
+  "split": "perturbation",
+  "rep_mode": "gene_op",
+  "match": "batch",
+  "d_pert": 64,
+  "hidden": 512,
+  "depth": 4,
+  "dropout": 0.0,
+  "lr": 0.001,
+  "weight_decay": 1e-05,
+  "batch_size": 1024,
+  "epochs": 45,
+  "lam_tan": 1.0,
+  "lam_semi": 0.5,
+  "lam_reg": 0.0001,
+  "grad_clip": 5.0,
+  "train_frac": 1.0,
+  "lam_dist": 0.0,
+  "n_dist_perts": 4,
+  "dist_n": 64,
+  "seed": 0,
+  "device_index": 3,
+  "components": [
+    "map"
+  ]
+}
\ No newline at end of file
diff --git a/models/ablations/norman_perturbation/comp_map/model.pt b/models/ablations/norman_perturbation/comp_map/model.pt
new file mode 100644
index 0000000000000000000000000000000000000000..f96ae7e48fd9f28a315e1d14b3487634520bed19
--- /dev/null
+++ b/models/ablations/norman_perturbation/comp_map/model.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d0fc420348d3e9e4ed59f6f36529905fa760793fd9cb0112a74caf8f02a2ce3e
+size 3575254
diff --git a/models/ablations/norman_perturbation/comp_map/train_info.json b/models/ablations/norman_perturbation/comp_map/train_info.json
new file mode 100644
index 0000000000000000000000000000000000000000..44d2637117daf44d14c5093435292ea9d20c0861
--- /dev/null
+++ b/models/ablations/norman_perturbation/comp_map/train_info.json
@@ -0,0 +1,322 @@
+{
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+}
\ No newline at end of file
diff --git a/models/ablations/norman_perturbation/comp_map_semi/config.json b/models/ablations/norman_perturbation/comp_map_semi/config.json
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,29 @@
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+  ]
+}
\ No newline at end of file
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diff --git a/models/ablations/norman_perturbation/comp_map_semi/train_info.json b/models/ablations/norman_perturbation/comp_map_semi/train_info.json
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diff --git a/models/norman/config.json b/models/norman/cell/config.json
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diff --git a/models/replogle_k562/config.json b/models/replogle_k562/cell/config.json
similarity index 100%
rename from models/replogle_k562/config.json
rename to models/replogle_k562/cell/config.json
diff --git a/models/replogle_k562/model.pt b/models/replogle_k562/cell/model.pt
similarity index 100%
rename from models/replogle_k562/model.pt
rename to models/replogle_k562/cell/model.pt
diff --git a/models/replogle_k562/train_info.json b/models/replogle_k562/cell/train_info.json
similarity index 99%
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\ No newline at end of file
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new file mode 100644
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\ No newline at end of file
diff --git a/models/replogle_k562/gene/model.pt b/models/replogle_k562/gene/model.pt
new file mode 100644
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+  "duration_s": 146.13456106185913,
+  "device": "cuda:3",
+  "n_train_cells": 89747
+}
\ No newline at end of file
diff --git a/models/replogle_k562/perturbation/config.json b/models/replogle_k562/perturbation/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2f8626f4ee6ca39f6389265f61d44644bafb8e4b
--- /dev/null
+++ b/models/replogle_k562/perturbation/config.json
@@ -0,0 +1,30 @@
+{
+  "dataset": "replogle_k562",
+  "embedding": "pca",
+  "split": "perturbation",
+  "rep_mode": "gene_op",
+  "match": "batch",
+  "d_pert": 64,
+  "hidden": 512,
+  "depth": 4,
+  "dropout": 0.0,
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+  "dist_n": 64,
+  "seed": 0,
+  "device_index": 3,
+  "components": [
+    "map",
+    "tan",
+    "semi"
+  ]
+}
\ No newline at end of file
diff --git a/models/replogle_k562/perturbation/model.pt b/models/replogle_k562/perturbation/model.pt
new file mode 100644
index 0000000000000000000000000000000000000000..297c6e17894edc763f240664810976e27a75f780
--- /dev/null
+++ b/models/replogle_k562/perturbation/model.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2fd29fbc5f3866dc03f28c90e3729617922ca683b9751b7d65e6cd828bc4fd5e
+size 4010454
diff --git a/models/replogle_k562/perturbation/train_info.json b/models/replogle_k562/perturbation/train_info.json
new file mode 100644
index 0000000000000000000000000000000000000000..94d5fc2f873c46c7654467b349206cdc554b90c1
--- /dev/null
+++ b/models/replogle_k562/perturbation/train_info.json
@@ -0,0 +1,427 @@
+{
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+  "duration_s": 154.79177355766296,
+  "device": "cuda:3",
+  "n_train_cells": 78836
+}
\ No newline at end of file
diff --git a/scripts/train_all.py b/scripts/train_all.py
new file mode 100644
index 0000000000000000000000000000000000000000..cb51168942a4cd274fbd91bd5871384f75a1f63b
--- /dev/null
+++ b/scripts/train_all.py
@@ -0,0 +1,49 @@
+# train every model behind the paper and keep the checkpoint (nothing discarded).
+# same configs and seed as the table/ablation runners, so the numbers reproduce.
+import os, sys
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
+from src.data.perturb_data import load_dataset, MATCH_STRATEGIES
+from src.models.encoders import REP_MODES
+from src.training.train import TrainConfig, train, save_checkpoint
+
+GPU = int(os.environ.get("PIVOT_GPU", "3"))
+ROOT = "models"
+
+
+def go(name, dataset, data, **cfgkw):
+    out = os.path.join(ROOT, name)
+    if os.path.exists(os.path.join(out, "model.pt")):
+        print("skip", name, flush=True); return
+    cfg = TrainConfig(dataset=dataset, device_index=GPU, **cfgkw)
+    model, info = train(cfg, data=data, verbose=False)
+    save_checkpoint(model, cfg, info, out)
+    print("saved", name, flush=True)
+
+
+# main table models: default config (epochs 60), one per dataset and split
+splits = {"norman": ["cell", "perturbation", "combination"],
+          "replogle_k562": ["cell", "perturbation", "gene"]}
+for ds, sps in splits.items():
+    data = load_dataset(ds)
+    for sp in sps:
+        go("%s/%s" % (ds, sp), ds, data, split=sp)
+
+# ablation models: norman, perturbation split, epochs 45 (matches run_ablations).
+# the "default" run here is the shared base for the inverse-search, guidance-step,
+# reward and cost ablations (they reuse one model), plus the components=full,
+# representation=gene_op, data-fraction=1.0 and matching=batch rows.
+data = load_dataset("norman")
+A = "ablations/norman_perturbation"
+go("%s/default" % A, "norman", data, split="perturbation", epochs=45)
+for nm, comps in [("comp_map", ["map"]), ("comp_map_semi", ["map", "semi"]), ("comp_map_tan", ["map", "tan"])]:
+    go("%s/%s" % (A, nm), "norman", data, split="perturbation", epochs=45, components=comps)
+for rep in REP_MODES:
+    if rep != "gene_op":
+        go("%s/rep_%s" % (A, rep), "norman", data, split="perturbation", epochs=45, rep_mode=rep)
+for frac in [0.1, 0.25, 0.5, 0.75]:
+    go("%s/frac_%s" % (A, frac), "norman", data, split="perturbation", epochs=45, train_frac=frac)
+for ms in MATCH_STRATEGIES:
+    if ms != "batch":
+        go("%s/match_%s" % (A, ms), "norman", data, split="perturbation", epochs=45, match=ms)
+
+print("TRAIN_ALL_DONE", flush=True)