diff --git a/hbw/config/defaults_and_groups.py b/hbw/config/defaults_and_groups.py
index c748a9b2..1a7e3fbc 100644
--- a/hbw/config/defaults_and_groups.py
+++ b/hbw/config/defaults_and_groups.py
@@ -60,7 +60,7 @@ def default_producers(cls, container, task_params):
     """ Default producers chosen based on the Inference model and the ML Model """
 
     # per default, use the ml_inputs and event_weights
-    default_producers = [ml_inputs_producer(container), "event_weights", "pre_ml_cats"]
+    default_producers = ["event_weights", "pre_ml_cats", ml_inputs_producer(container)]
 
     if hasattr(cls, "ml_model"):
         # do no further resolve the ML categorizer when this task is part of the MLTraining pipeline
@@ -127,22 +127,22 @@ def set_config_defaults_and_groups(config_inst):
     # (used in wrapper_factory and during plotting)
     config_inst.x.process_groups = {
         "all": ["*"],
-        "default": [default_signal_process, "tt", "st", "w_lnu", "dy_lep"],
-        "with_qcd": [default_signal_process, "tt", "qcd", "st", "w_lnu", "dy_lep"],
-        "much": [default_signal_process, "tt", "qcd_mu", "st", "w_lnu", "dy_lep"],
-        "2much": [default_signal_process, "tt", "st", "w_lnu", "dy_lep"],
-        "ech": [default_signal_process, "tt", "qcd_ele", "st", "w_lnu", "dy_lep"],
-        "2ech": [default_signal_process, "tt", "st", "w_lnu", "dy_lep"],
-        "emuch": [default_signal_process, "tt", "st", "w_lnu", "dy_lep"],
-        "inference": ["hh_ggf_*", "tt", "st", "w_lnu", "dy_lep", "qcd_*"],
-        "k2v": ["hh_vbf_*", "tt", "st", "w_lnu", "dy_lep", "qcd_*"],
-        "ml": [default_signal_process, "tt", "st", "w_lnu", "dy_lep"],
+        "default": [default_signal_process, "tt", "st", "w_lnu", "dy"],
+        "with_qcd": [default_signal_process, "tt", "qcd", "st", "w_lnu", "dy"],
+        "much": [default_signal_process, "tt", "qcd_mu", "st", "w_lnu", "dy"],
+        "2much": [default_signal_process, "tt", "st", "w_lnu", "dy"],
+        "ech": [default_signal_process, "tt", "qcd_ele", "st", "w_lnu", "dy"],
+        "2ech": [default_signal_process, "tt", "st", "w_lnu", "dy"],
+        "emuch": [default_signal_process, "tt", "st", "w_lnu", "dy"],
+        "inference": ["hh_ggf_*", "tt", "st", "w_lnu", "dy", "qcd_*"],
+        "k2v": ["hh_vbf_*", "tt", "st", "w_lnu", "dy", "qcd_*"],
+        "ml": [default_signal_process, "tt", "st", "w_lnu", "dy"],
         "ml_test": [default_signal_process, "st", "w_lnu"],
-        "mldl": ["hh_ggf_kl1_kt1_hbb_hvv2l2nu", "tt", "st", "dy_lep"],
-        "mlsl": ["hh_ggf_kl1_kt1_hbb_hvvqqlnu", "tt", "st", "w_lnu", "dy_lep"],
+        "mldl": ["hh_ggf_kl1_kt1_hbb_hvv2l2nu", "tt", "st", "dy"],
+        "mlsl": ["hh_ggf_kl1_kt1_hbb_hvvqqlnu", "tt", "st", "w_lnu", "dy"],
         "test": [default_signal_process, "tt_sl"],
         "small": [default_signal_process, "tt", "st"],
-        "bkg": ["tt", "st", "w_lnu", "dy_lep"],
+        "bkg": ["tt", "st", "w_lnu", "dy"],
         "signal": ["hh_ggf_*", "hh_vbf_*"], "hh_ggf": ["hh_ggf_*"], "hh_vbf": ["hh_vbf_*"],
     }
     config_inst.x.process_groups["dmuch"] = ["data_mu"] + config_inst.x.process_groups["much"]
@@ -170,12 +170,16 @@ def set_config_defaults_and_groups(config_inst):
     # category groups for conveniently looping over certain categories
     # (used during plotting and for rebinning)
     config_inst.x.category_groups = {
+        "sl": ["sr__1e", "sr__1mu"],
+        "sl_resolved": ["sr__1e__resolved", "sr__1mu__resolved"],
         "sl_much": ["sr__1mu", "sr__1mu__resolved", "sr__1mu__boosted"],
         "sl_ech": ["sr__1e", "sr__1e__resolved", "sr__1e__boosted"],
         "sl_much_resolved": ["sr__1mu__resolved", "sr__1mu__resolved__1b", "sr__1mu__resolved__2b"],
         "sl_ech_resolved": ["sr__1e__resolved", "sr__1e__resolved__1b", "sr__1e__resolved__2b"],
         "sl_much_boosted": ["sr__1mu__boosted"],
         "sl_ech_boosted": ["sr__1e__boosted"],
+        "dl": ["sr__2e", "sr__2mu", "sr__emu"],
+        "dl_resolved": ["sr__2e__resolved", "sr__2mu__resolved", "sr__emu__resolved"],
         "dl_2much": ["sr__2mu", "sr__2mu__resolved", "sr__2mu__boosted"],
         "dl_2ech": ["sr__2e", "sr__2e__resolved", "sr__2e__boosted"],
         "dl_emuch": ["sr__emu", "sr__emu__resolved", "sr__emu__boosted"],
@@ -227,9 +231,9 @@ def set_config_defaults_and_groups(config_inst):
             "sr__emu__1b__ml_hh_ggf_kl1_kt1_hbb_hvv2l2nu", "sr__emu__2b__ml_hh_ggf_kl1_kt1_hbb_hvv2l2nu",
         ),
         "BR_dl": (
-            "sr__2e__ml_tt", "sr__2e__ml_st", "sr__2e__ml_dy_lep",
-            "sr__2mu__ml_tt", "sr__2mu__ml_st", "sr__2mu__ml_dy_lep",
-            "sr__emu__ml_tt", "sr__emu__ml_st", "sr__emu__ml_dy_lep",
+            "sr__2e__ml_tt", "sr__2e__ml_st", "sr__2e__ml_dy",
+            "sr__2mu__ml_tt", "sr__2mu__ml_st", "sr__2mu__ml_dy",
+            "sr__emu__ml_tt", "sr__emu__ml_st", "sr__emu__ml_dy",
         ),
     }
 
@@ -299,7 +303,7 @@ def set_config_defaults_and_groups(config_inst):
         },
     }
     # when drawing DY as a line, use a different type of yellow
-    config_inst.x.process_settings_groups["unstack_all"].update({"dy_lep": {"unstack": True, "color": "#e6d800"}})
+    config_inst.x.process_settings_groups["unstack_all"].update({"dy": {"unstack": True, "color": "#e6d800"}})
 
     config_inst.x.variable_settings_groups = {
         "test": {
diff --git a/hbw/config/processes.py b/hbw/config/processes.py
index dac4ba1f..c4c07fba 100644
--- a/hbw/config/processes.py
+++ b/hbw/config/processes.py
@@ -50,7 +50,7 @@ def add_dummy_xsecs(config: od.Config, dummy_xsec: float = 0.1):
             process_inst.xsecs[ecm] = Number(dummy_xsec)
 
     # # temporary xsecs from XSDB
-    # config.get_process("dy_lep").xsecs[13.6] = Number(67710.0)  # https://xsdb-temp.app.cern.ch/xsdb/?columns=37814272&currentPage=0&pageSize=10&searchQuery=DAS%3DWtoLNu-2Jets_TuneCP5_13p6TeV_amcatnloFXFX-pythia8  # noqa
+    # config.get_process("dy").xsecs[13.6] = Number(67710.0)  # https://xsdb-temp.app.cern.ch/xsdb/?columns=37814272&currentPage=0&pageSize=10&searchQuery=DAS%3DWtoLNu-2Jets_TuneCP5_13p6TeV_amcatnloFXFX-pythia8  # noqa
     # config.get_process("w_lnu").xsecs[13.6] = Number(5558.0)  # https://xsdb-temp.app.cern.ch/xsdb/?columns=37814272&currentPage=0&ordDirection=1&ordFieldName=process_name&pageSize=10&searchQuery=DAS%3DWtoLNu-2Jets_TuneCP5_13p6TeV_amcatnloFXFX-pythia8  # noqa
 
     # temporary xsecs that were missing in xsdb
@@ -93,11 +93,11 @@ def configure_hbw_processes(config: od.Config):
 
     # custom v_lep process for ML Training, combining W+DY
     w_lnu = config.get_process("w_lnu", default=None)
-    dy_lep = config.get_process("dy_lep", default=None)
-    if w_lnu and dy_lep:
+    dy = config.get_process("dy", default=None)
+    if w_lnu and dy:
         v_lep = add_parent_process(  # noqa
             config,
-            [w_lnu, dy_lep],
+            [w_lnu, dy],
             name="v_lep",
             id=64575573,  # random number
             label="W and DY",
diff --git a/hbw/config/styling.py b/hbw/config/styling.py
index 40cca001..7d546904 100644
--- a/hbw/config/styling.py
+++ b/hbw/config/styling.py
@@ -25,7 +25,7 @@
     "higgs": "#984ea3",  # purple
     "st": "#ff7f00",  # orange
     "t_bkg": "#e41a1c",  # orange
-    "dy_lep": "#ffff33",  # yellow
+    "dy": "#ffff33",  # yellow
     "ttV": "#a65628",  # brown
     "VV": "#f781bf",  # pink
     "other": "#999999",  # grey
@@ -71,7 +71,7 @@
     "graviton_hh_ggf_bbww_m1000": "grav1000",
     "st": "st",
     "w_lnu": "W",
-    "dy_lep": "DY",
+    "dy": "DY",
     "v_lep": "W+DY",
     "t_bkg": "tt+st",
 }
@@ -101,7 +101,7 @@
     "hh_vbf_kv0p5_k2v1_kl1_hbb_hvv2l2nu": r"$HH_{vbf}^{0.5,1,1} (DL)$",
     "hh_vbf_kv1p5_k2v1_kl1_hbb_hvv2l2nu": r"$HH_{vbf}^{1.5,1,1} (DL)$",
     "w_lnu": r"$W \rightarrow l\nu$",
-    "dy_lep": r"$Z \rightarrow ll$",
+    "dy": r"$Z \rightarrow ll$",
     "qcd_mu": r"$QCD \mu$",
     "qcd_ele": r"$QCD e$",
 }
diff --git a/hbw/inference/constants.py b/hbw/inference/constants.py
index d1f80cd7..79648dbb 100644
--- a/hbw/inference/constants.py
+++ b/hbw/inference/constants.py
@@ -42,7 +42,7 @@
 # mapping, which processes are used for which QCDScale (rate) uncertainty
 processes_per_QCDScale = {
     "ttbar": ["tt", "st_tchannel", "st_schannel", "st_twchannel", "ttW", "ttZ"],
-    "V": ["dy_lep", "w_lnu"],
+    "V": ["dy", "w_lnu"],
     "VV": ["WW", "ZZ", "WZ", "qqZZ"],
     "VVV": ["vvv"],
     "ggH": ["ggH"],
@@ -59,7 +59,7 @@
 # mapping, which processes are used for which pdf (rate) uncertainty
 processes_per_pdf_rate = {
     "gg": ["tt", "ttZ", "ggZZ"],
-    "qqbar": ["st_schannel", "st_tchannel", "dy_lep", "w_lnu", "vvv", "qqZZ", "ttW"],
+    "qqbar": ["st_schannel", "st_tchannel", "dy", "w_lnu", "vvv", "qqZZ", "ttW"],
     "qg": ["st_twchannel"],
     "Higgs_gg": ["ggH"],
     "Higgs_qqbar": ["qqH", "ZH", "WH", "VH"],
@@ -100,7 +100,7 @@
     "pdf_shape_hh_ggf_kl5_kt1_hbb_hvv2l2nu": ["hh_ggf_kl5_kt1_hbb_hvv2l2nu"],
     "pdf_shape_tt": ["tt"],
     "pdf_shape_st": ["st_schannel", "st_twchannel"],  # TODO: there was some bug with "st_tchannel"
-    "pdf_shape_dy": ["dy_lep"],
+    "pdf_shape_dy": ["dy"],
     "pdf_shape_w": ["w_lnu"],
     "murf_envelope_hh_ggf_kl0_kt1_hbb_hvvqqlnu": ["hh_ggf_kl0_kt1_hbb_hvvqqlnu"],
     "murf_envelope_hh_ggf_kl1_kt1_hbb_hvvqqlnu": ["hh_ggf_kl1_kt1_hbb_hvvqqlnu"],
@@ -112,7 +112,7 @@
     "murf_envelope_hh_ggf_kl5_kt1_hbb_hvv2l2nu": ["hh_ggf_kl5_kt1_hbb_hvv2l2nu"],
     "murf_envelope_tt": ["tt"],
     "murf_envelope_st": ["st_schannel", "st_tchannel", "st_twchannel"],
-    "murf_envelope_dy": ["dy_lep"],
+    "murf_envelope_dy": ["dy"],
     "murf_envelope_w": ["w_lnu"],
 }
 
diff --git a/hbw/inference/dl.py b/hbw/inference/dl.py
index 98fdac21..00a828dc 100644
--- a/hbw/inference/dl.py
+++ b/hbw/inference/dl.py
@@ -25,7 +25,7 @@
     "tt",
     # "ttv", "ttvv",
     "st_schannel", "st_tchannel", "st_twchannel",
-    "dy_lep",
+    "dy",
     "w_lnu",
     # "vv",
     # "vvv",
@@ -93,14 +93,14 @@
     # "murf_envelope_hh_ggf_kl1_kt1_hbb_hvv2l2nu",
     "murf_envelope_tt",
     "murf_envelope_st",
-    "murf_envelope_dy_lep",
+    "murf_envelope_dy",
     "murf_envelope_w_lnu",
     "murf_envelope_ttV",
     "murf_envelope_VV",
     # Shape PDF Uncertainties
     "pdf_shape_tt",
     "pdf_shape_st",
-    "pdf_shape_dy_lep",
+    "pdf_shape_dy",
     "pdf_shape_w_lnu",
     "pdf_shape_ttV",
     "pdf_shape_VV",
@@ -169,7 +169,7 @@
     "tt",
     # "st_schannel",
     "st_tchannel", "st_twchannel",
-    "dy_lep",
+    "dy",
     "w_lnu",
 ]
 
@@ -184,13 +184,13 @@
     # Background regions
     "sr__2e__ml_tt",
     "sr__2e__ml_st",
-    "sr__2e__ml_dy_lep",
+    "sr__2e__ml_dy",
     "sr__2mu__ml_tt",
     "sr__2mu__ml_st",
-    "sr__2mu__ml_dy_lep",
+    "sr__2mu__ml_dy",
     "sr__emu__ml_tt",
     "sr__emu__ml_st",
-    "sr__emu__ml_dy_lep",
+    "sr__emu__ml_dy",
 ]
 
 dl_22 = dl.derive("dl_22", cls_dict={
diff --git a/hbw/inference/old_model.py b/hbw/inference/old_model.py
index 614b292f..d1d42133 100644
--- a/hbw/inference/old_model.py
+++ b/hbw/inference/old_model.py
@@ -28,7 +28,7 @@ def default(self):
         "tt",
         "st",
         "w_lnu",
-        "dy_lep",
+        "dy",
     ]
 
     for proc in ml_model_processes:
@@ -69,7 +69,7 @@ def default(self):
         "tt",
         # "ttv", "ttvv",
         "st_schannel", "st_tchannel", "st_twchannel",
-        "dy_lep",
+        "dy",
         "w_lnu",
         # "vv",
         # "vvv",
@@ -112,7 +112,7 @@ def default(self):
     # add QCD scale uncertainties to inference model
     proc_QCDscale = {
         "ttbar": ["tt", "st_tchannel", "st_schannel", "st_twchannel", "ttW", "ttZ"],
-        "V": ["dy_lep", "w_lnu"],
+        "V": ["dy", "w_lnu"],
         "VV": ["WW", "ZZ", "WZ", "qqZZ"],
         "VVV": ["vvv"],
         "ggH": ["ggH"],
@@ -151,7 +151,7 @@ def default(self):
     # add PDF rate uncertainties to inference model
     proc_pdf = {
         "gg": ["tt", "ttZ", "ggZZ"],
-        "qqbar": ["st_schannel", "st_tchannel", "dy_lep", "w_lnu", "vvv", "qqZZ", "ttW"],
+        "qqbar": ["st_schannel", "st_tchannel", "dy", "w_lnu", "vvv", "qqZZ", "ttW"],
         "qg": ["st_twchannel"],
         "Higgs_gg": ["ggH"],
         "Higgs_qqbar": ["qqH", "ZH", "WH", "VH"],
diff --git a/hbw/inference/sl.py b/hbw/inference/sl.py
index eb319a02..b9d59c08 100644
--- a/hbw/inference/sl.py
+++ b/hbw/inference/sl.py
@@ -26,7 +26,7 @@
     "tt",
     # "ttv", "ttvv",
     "st_schannel", "st_tchannel", "st_twchannel",
-    "dy_lep",
+    "dy",
     "w_lnu",
     # "vv",
     # "vvv",
@@ -92,14 +92,14 @@
     # "murf_envelope_hh_ggf_kl1_kt1_hbb_hvv2l2nu",
     "murf_envelope_tt",
     "murf_envelope_st",
-    "murf_envelope_dy_lep",
+    "murf_envelope_dy",
     "murf_envelope_w_lnu",
     "murf_envelope_ttV",
     "murf_envelope_VV",
     # Shape PDF Uncertainties
     "pdf_shape_tt",
     "pdf_shape_st",
-    "pdf_shape_dy_lep",
+    "pdf_shape_dy",
     "pdf_shape_w_lnu",
     "pdf_shape_ttV",
     "pdf_shape_VV",
@@ -176,7 +176,7 @@
     "tt",
     # "st_schannel",
     "st_tchannel", "st_twchannel",
-    "dy_lep",
+    "dy",
     "w_lnu",
 ]
 
diff --git a/hbw/inference/sl_res.py b/hbw/inference/sl_res.py
index 826f8227..abdc6ca7 100644
--- a/hbw/inference/sl_res.py
+++ b/hbw/inference/sl_res.py
@@ -52,7 +52,7 @@ def add_inference_categories(self: InferenceModel):
     "graviton_hh_ggf_bbww_m600",
     "tt",
     "st",
-    "dy_lep",
+    "dy",
     "w_lnu",
     # "v_lep",
     # "t_bkg",
@@ -64,7 +64,7 @@ def add_inference_categories(self: InferenceModel):
     "cat__1e_graviton_hh_ggf_bbww_m600",
     # "1e__ml_tt",
     # "1e__ml_st",
-    # "1e__ml_dy_lep",
+    # "1e__ml_dy",
     # "1e__ml_w_lnu",
     "1e__ml_v_lep",
     "1e__ml_t_bkg",
@@ -72,7 +72,7 @@ def add_inference_categories(self: InferenceModel):
     "1mu__ml_graviton_hh_ggf_bbww_m600",
     # "1mu__ml_tt",
     # "1mu__ml_st",
-    # "1mu__ml_dy_lep",
+    # "1mu__ml_dy",
     # "1mu__ml_w_lnu",
     "1mu__ml_v_lep",
     "1mu__ml_t_bkg",
@@ -83,7 +83,7 @@ def add_inference_categories(self: InferenceModel):
     "1e_graviton_hh_ggf_bbww_m600",
     # "1e__ml_tt",
     # "1e__ml_st",
-    # "1e__ml_dy_lep",
+    # "1e__ml_dy",
     # "1e__ml_w_lnu",
     "1e__ml_v_lep",
     "1e__ml_t_bkg",
@@ -91,7 +91,7 @@ def add_inference_categories(self: InferenceModel):
     "1mu__ml_graviton_hh_ggf_bbww_m600",
     # "1mu__ml_tt",
     # "1mu__ml_st",
-    # "1mu__ml_dy_lep",
+    # "1mu__ml_dy",
     # "1mu__ml_w_lnu",
     "1mu__ml_v_lep",
     "1mu__ml_t_bkg",
@@ -139,7 +139,7 @@ def add_inference_categories(self: InferenceModel):
     # "murf_envelope_st_schannel",
     # "murf_envelope_st_tchannel",
     # "murf_envelope_st_twchannel",
-    # "murf_envelope_dy_lep",
+    # "murf_envelope_dy",
     # "murf_envelope_w_lnu",
     # "murf_envelope_ttV",
     # "murf_envelope_VV",
@@ -148,7 +148,7 @@ def add_inference_categories(self: InferenceModel):
     # "pdf_shape_st_schannel",
     # "pdf_shape_st_tchannel",
     # "pdf_shape_st_twchannel",
-    # "pdf_shape_dy_lep",
+    # "pdf_shape_dy",
     # "pdf_shape_w_lnu",
     # "pdf_shape_ttV",
     # "pdf_shape_VV",
@@ -193,7 +193,7 @@ def add_inference_categories(self: InferenceModel):
         f"graviton_hh_ggf_bbww_m{m}",
         "tt",
         "st",
-        "dy_lep",
+        "dy",
         "w_lnu",
     ]
 
@@ -215,12 +215,12 @@ def add_inference_categories(self: InferenceModel):
         f"1e__ml_graviton_hh_ggf_bbww_m{m}",
         "1e__ml_tt",
         "1e__ml_st",
-        "1e__ml_dy_lep",
+        "1e__ml_dy",
         "1e__ml_w_lnu",
         f"1mu__ml_graviton_hh_ggf_bbww_m{m}",
         "1mu__ml_tt",
         "1mu__ml_st",
-        "1mu__ml_dy_lep",
+        "1mu__ml_dy",
         "1mu__ml_w_lnu",
     ]
     ml_model_name = f"dense_graviton{m}"
diff --git a/hbw/ml/derived/dl.py b/hbw/ml/derived/dl.py
index 8b28c504..457ef46c 100644
--- a/hbw/ml/derived/dl.py
+++ b/hbw/ml/derived/dl.py
@@ -27,7 +27,7 @@ class DenseClassifierDL(DenseModelMixin, ModelFitMixin, MLClassifierBase):
         "sig",
         "tt",
         "st",
-        "dy_lep",
+        "dy",
     )
 
     ml_process_weights = {
@@ -41,7 +41,7 @@ class DenseClassifierDL(DenseModelMixin, ModelFitMixin, MLClassifierBase):
         "v_lep": 2,
         "tt_bkg": 2,
         "w_lnu": 2,
-        "dy_lep": 2,
+        "dy": 2,
     }
 
     input_features = [
@@ -160,7 +160,7 @@ def setup(self):
 
 dl_22post = DenseClassifierDL.derive("dl_22post", cls_dict={
     "training_configs": lambda self, requested_configs: ["c22post"],
-    "processes": ["hh_ggf_kl1_kt1_hbb_hvv2l2nu", "tt", "st", "dy_lep"],
+    "processes": ["hh_ggf_kl1_kt1_hbb_hvv2l2nu", "tt", "st", "dy"],
 })
 dl_22post_test = dl_22post.derive("dl_22post_test", cls_dict={
     "processes": ["hh_ggf_kl1_kt1_hbb_hvv2l2nu", "st_tchannel_t"],
@@ -171,11 +171,11 @@ def setup(self):
 })
 dl_22 = DenseClassifierDL.derive("dl_22", cls_dict={
     "training_configs": lambda self, requested_configs: ["c22post", "c22pre"],
-    "processes": ["hh_ggf_kl1_kt1_hbb_hvv2l2nu", "tt", "st", "dy_lep"],
+    "processes": ["hh_ggf_kl1_kt1_hbb_hvv2l2nu", "tt", "st", "dy"],
 })
 dl_17 = DenseClassifierDL.derive("dl_17", cls_dict={
     "training_configs": lambda self, requested_configs: ["c17"],
-    "processes": ["sig", "tt", "st", "dy_lep"],
+    "processes": ["sig", "tt", "st", "dy"],
 })
 
 # testing of hyperparameter changes
diff --git a/hbw/ml/derived/grid_search.py b/hbw/ml/derived/grid_search.py
index 48de5415..2c3ebbae 100644
--- a/hbw/ml/derived/grid_search.py
+++ b/hbw/ml/derived/grid_search.py
@@ -16,7 +16,7 @@
     "st": bkg_weight,
     "v_lep": bkg_weight,
     "w_lnu": bkg_weight,
-    "dy_lep": bkg_weight,
+    "dy": bkg_weight,
 }
 
 example_grid_search = {  # 4*2*2*1*3*3*1 = 144 trainings
diff --git a/hbw/ml/derived/sl.py b/hbw/ml/derived/sl.py
index c7d832ca..65f6c1fc 100644
--- a/hbw/ml/derived/sl.py
+++ b/hbw/ml/derived/sl.py
@@ -30,7 +30,7 @@ class DenseClassifierSL(ModelFitMixin, DenseModelMixin, MLClassifierBase):
         "st",
         "v_lep",
         # "w_lnu",
-        # "dy_lep",
+        # "dy",
     ]
 
     ml_process_weights: dict = {
@@ -40,7 +40,7 @@ class DenseClassifierSL(ModelFitMixin, DenseModelMixin, MLClassifierBase):
         "st": 2,
         "v_lep": 2,
         "w_lnu": 2,
-        "dy_lep": 2,
+        "dy": 2,
     }
 
     input_features: list = [
diff --git a/hbw/ml/derived/sl_res.py b/hbw/ml/derived/sl_res.py
index e8fd109d..100f41e5 100644
--- a/hbw/ml/derived/sl_res.py
+++ b/hbw/ml/derived/sl_res.py
@@ -29,7 +29,7 @@ class DenseClassifierRes(ModelFitMixin, DenseModelMixin, MLClassifierBase):
         # "tt",
         # "st",
         # "w_lnu",
-        # "dy_lep",
+        # "dy",
         "t_bkg",
         "v_lep",
 
@@ -40,7 +40,7 @@ class DenseClassifierRes(ModelFitMixin, DenseModelMixin, MLClassifierBase):
         # "tt": 8,
         # "st": 8,
         # "w_lnu": 8,
-        # "dy_lep": 8,
+        # "dy": 8,
         "t_bkg": 1,
         "v_lep": 1,
     }
@@ -68,14 +68,14 @@ class DenseClassifierRes(ModelFitMixin, DenseModelMixin, MLClassifierBase):
         "w_lnu_ht1200To2500_madgraph",
         "w_lnu_ht2500_madgraph",
         # DY
-        "dy_lep_m50_ht70to100_madgraph",
-        "dy_lep_m50_ht100to200_madgraph",
-        "dy_lep_m50_ht200to400_madgraph",
-        "dy_lep_m50_ht400to600_madgraph",
-        "dy_lep_m50_ht600to800_madgraph",
-        "dy_lep_m50_ht800to1200_madgraph",
-        "dy_lep_m50_ht1200to2500_madgraph",
-        "dy_lep_m50_ht2500_madgraph",
+        "dy_m50_ht70to100_madgraph",
+        "dy_m50_ht100to200_madgraph",
+        "dy_m50_ht200to400_madgraph",
+        "dy_m50_ht400to600_madgraph",
+        "dy_m50_ht600to800_madgraph",
+        "dy_m50_ht800to1200_madgraph",
+        "dy_m50_ht1200to2500_madgraph",
+        "dy_m50_ht2500_madgraph",
     }
 
     input_features = [
@@ -220,7 +220,7 @@ def training_producers(self, config_inst: od.Config, requested_producers: Sequen
         # "tt",
         # "st",
         # "w_lnu",
-        # "dy_lep",
+        # "dy",
         "t_bkg",
         "v_lep",
     ]
@@ -229,7 +229,7 @@ def training_producers(self, config_inst: od.Config, requested_producers: Sequen
         # "tt": 8,
         # "st": 8,
         # "w_lnu": 8,
-        # "dy_lep": 8,
+        # "dy": 8,
         "t_bkg": 1,
         "v_lep": 1,
     }
@@ -256,14 +256,14 @@ def training_producers(self, config_inst: od.Config, requested_producers: Sequen
         "w_lnu_ht1200To2500_madgraph",
         "w_lnu_ht2500_madgraph",
         # DY
-        "dy_lep_m50_ht70to100_madgraph",
-        "dy_lep_m50_ht100to200_madgraph",
-        "dy_lep_m50_ht200to400_madgraph",
-        "dy_lep_m50_ht400to600_madgraph",
-        "dy_lep_m50_ht600to800_madgraph",
-        "dy_lep_m50_ht800to1200_madgraph",
-        "dy_lep_m50_ht1200to2500_madgraph",
-        "dy_lep_m50_ht2500_madgraph",
+        "dy_m50_ht70to100_madgraph",
+        "dy_m50_ht100to200_madgraph",
+        "dy_m50_ht200to400_madgraph",
+        "dy_m50_ht400to600_madgraph",
+        "dy_m50_ht600to800_madgraph",
+        "dy_m50_ht800to1200_madgraph",
+        "dy_m50_ht1200to2500_madgraph",
+        "dy_m50_ht2500_madgraph",
     }
     cls_dict_res = {
         "processes": processes,
diff --git a/hbw/ml/old_ml_model.py b/hbw/ml/old_ml_model.py
index 3ab28473..12d95f5c 100644
--- a/hbw/ml/old_ml_model.py
+++ b/hbw/ml/old_ml_model.py
@@ -533,7 +533,7 @@ def evaluate(
     "tt",
     "st",
     "w_lnu",
-    "dy_lep",
+    "dy",
 ]
 
 custom_procweights = {
@@ -541,7 +541,7 @@ def evaluate(
     "tt": 8,
     "st": 8,
     "w_lnu": 8,
-    "dy_lep": 8,
+    "dy": 8,
 }
 
 dataset_names = {
@@ -567,14 +567,14 @@ def evaluate(
     "w_lnu_ht1200To2500_madgraph",
     "w_lnu_ht2500_madgraph",
     # DY
-    "dy_lep_m50_ht70to100_madgraph",
-    "dy_lep_m50_ht100to200_madgraph",
-    "dy_lep_m50_ht200to400_madgraph",
-    "dy_lep_m50_ht400to600_madgraph",
-    "dy_lep_m50_ht600to800_madgraph",
-    "dy_lep_m50_ht800to1200_madgraph",
-    "dy_lep_m50_ht1200to2500_madgraph",
-    "dy_lep_m50_ht2500_madgraph",
+    "dy_m50_ht70to100_madgraph",
+    "dy_m50_ht100to200_madgraph",
+    "dy_m50_ht200to400_madgraph",
+    "dy_m50_ht400to600_madgraph",
+    "dy_m50_ht600to800_madgraph",
+    "dy_m50_ht800to1200_madgraph",
+    "dy_m50_ht1200to2500_madgraph",
+    "dy_m50_ht2500_madgraph",
 }
 
 input_features = [
diff --git a/hbw/scripts/hbwtasks.sh b/hbw/scripts/hbwtasks.sh
index c1468d79..07ac83f4 100644
--- a/hbw/scripts/hbwtasks.sh
+++ b/hbw/scripts/hbwtasks.sh
@@ -210,7 +210,7 @@ hbw_plot_variables(){
 }
 
 ml_output_variables="mlscore.*"
-ml_categories="resolved,boosted,incl,ml_hh_ggf_kl1_kt1_hbb_hvvqqlnu,ml_tt,ml_st,ml_w_lnu,ml_dy_lep"
+ml_categories="resolved,boosted,incl,ml_hh_ggf_kl1_kt1_hbb_hvvqqlnu,ml_tt,ml_st,ml_w_lnu,ml_dy"
 
 hbw_plot_ml_nodes(){
     law run cf.PlotVariables1D --version $version \
diff --git a/hbw/selection/categories.py b/hbw/selection/categories.py
index 83083d69..200a7243 100644
--- a/hbw/selection/categories.py
+++ b/hbw/selection/categories.py
@@ -272,7 +272,7 @@ def catid_2b(self: Categorizer, events: ak.Array, **kwargs) -> tuple[ak.Array, a
 # TODO: not hard-coded -> use config?
 ml_processes = [
     "hh_ggf_kl1_kt1_hbb_hvvqqlnu", "hh_vbf_kv1_k2v1_kl1_hbb_hvvqqlnu",
-    "tt", "st", "w_lnu", "dy_lep", "v_lep",
+    "tt", "st", "w_lnu", "dy", "v_lep",
     "hh_ggf_kl1_kt1_hbb_hvv2l2nu", "t_bkg", "sig",
     "graviton_hh_ggf_bbww_m250", "graviton_hh_ggf_bbww_m350", "graviton_hh_ggf_bbww_m450",
     "graviton_hh_ggf_bbww_m600", "graviton_hh_ggf_bbww_m750", "graviton_hh_ggf_bbww_m1000",
diff --git a/hbw/util.py b/hbw/util.py
index 1720065c..7c0132a2 100644
--- a/hbw/util.py
+++ b/hbw/util.py
@@ -7,7 +7,7 @@
 from __future__ import annotations
 
 import time
-from typing import Hashable, Iterable, Callable, Any
+from typing import Hashable, Iterable, Callable
 from functools import wraps
 import tracemalloc