diff --git a/.DS_Store b/.DS_Store
new file mode 100644
index 00000000..98053944
Binary files /dev/null and b/.DS_Store differ
diff --git a/skglm/estimators.py b/skglm/estimators.py
index 870b1cbe..6197101c 100644
--- a/skglm/estimators.py
+++ b/skglm/estimators.py
@@ -448,6 +448,11 @@ def path(self, X, y, alphas, coef_init=None, return_n_iter=True, **params):
             warm_start=self.warm_start, verbose=self.verbose)
         return solver.path(X, y, datafit, penalty, alphas, coef_init, return_n_iter)
 
+    def __sklearn_tags__(self):
+        tags = super().__sklearn_tags__()
+        tags.input_tags.sparse = True
+        return tags
+
 
 class WeightedLasso(RegressorMixin, LinearModel):
     r"""WeightedLasso estimator based on Celer solver and primal extrapolation.
@@ -611,6 +616,11 @@ def fit(self, X, y):
             warm_start=self.warm_start, verbose=self.verbose)
         return _glm_fit(X, y, self, Quadratic(), penalty, solver)
 
+    def __sklearn_tags__(self):
+        tags = super().__sklearn_tags__()
+        tags.input_tags.sparse = True
+        return tags
+
 
 class ElasticNet(RegressorMixin, LinearModel):
     r"""Elastic net estimator.
@@ -765,6 +775,11 @@ def fit(self, X, y):
         return _glm_fit(X, y, self, Quadratic(),
                         L1_plus_L2(self.alpha, self.l1_ratio, self.positive), solver)
 
+    def __sklearn_tags__(self):
+        tags = super().__sklearn_tags__()
+        tags.input_tags.sparse = True
+        return tags
+
 
 class MCPRegression(RegressorMixin, LinearModel):
     r"""Linear regression with MCP penalty estimator.
@@ -953,6 +968,11 @@ def fit(self, X, y):
             warm_start=self.warm_start, verbose=self.verbose)
         return _glm_fit(X, y, self, Quadratic(), penalty, solver)
 
+    def __sklearn_tags__(self):
+        tags = super().__sklearn_tags__()
+        tags.input_tags.sparse = True
+        return tags
+
 
 class SparseLogisticRegression(LinearClassifierMixin, SparseCoefMixin, BaseEstimator):
     r"""Sparse Logistic regression estimator.
@@ -1380,6 +1400,11 @@ def fit(self, X, y):
 
         return self
 
+    def __sklearn_tags__(self):
+        tags = super().__sklearn_tags__()
+        tags.input_tags.sparse = True
+        return tags
+
 
 class MultiTaskLasso(RegressorMixin, LinearModel):
     r"""MultiTaskLasso estimator.