diff --git a/keras/layers/core.py b/keras/layers/core.py
index 5131f52fa..726b76caa 100644
--- a/keras/layers/core.py
+++ b/keras/layers/core.py
@@ -289,7 +289,8 @@ class Merge(Layer):
         if mode in {'sum', 'mul', 'ave', 'cos'}:
             input_shapes = set([l.output_shape for l in layers])
             if len(input_shapes) > 1:
-                raise Exception("Only layers of same output shape can be merged using " + mode + " mode")
+                raise Exception("Only layers of same output shape can be merged using " + mode + " mode. " +
+                                "Layer shapes: %s" % ([l.output_shape for l in layers]))
         if mode in {'cos', 'dot'}:
             if len(layers) > 2:
                 raise Exception(mode + " merge takes exactly 2 layers")
@@ -303,9 +304,17 @@ class Merge(Layer):
                         dot_axes = [range(dot_axes % n1, n1), range(dot_axes % n2, n2)]
                     else:
                         dot_axes = [range(n1 - dot_axes, n2), range(1, dot_axes + 1)]
+                if type(dot_axes) not in [list, tuple]:
+                    raise Exception("Invalid type for dot_axes - should be a list.")
+                if len(dot_axes) != 2:
+                    raise Exception("Invalid format for dot_axes - should contain two elements.")
+                if type(dot_axes[0]) not in [list, tuple, range] or type(dot_axes[1]) not in [list, tuple, range]:
+                    raise Exception("Invalid format for dot_axes - list elements should have type 'list' or 'tuple'.")
                 for i in range(len(dot_axes[0])):
                     if shape1[dot_axes[0][i]] != shape2[dot_axes[1][i]]:
-                        raise Exception(" Dot incompatible layers can not be merged using dot mode")
+                        raise Exception("Dimension incompatibility using dot mode: " +
+                                        "%s != %s. " % (shape1[dot_axes[0][i]], shape2[dot_axes[1][i]]) +
+                                        "Layer shapes: %s, %s" % (shape1, shape2))
         elif mode == 'concat':
             input_shapes = set()
             for l in layers:
@@ -314,7 +323,9 @@ class Merge(Layer):
                 oshape = tuple(oshape)
                 input_shapes.add(oshape)
             if len(input_shapes) > 1:
-                raise Exception("'concat' mode can only merge layers with matching output shapes except for the concat axis")
+                raise Exception("'concat' mode can only merge layers with matching " +
+                                "output shapes except for the concat axis. " +
+                                "Layer shapes: %s" % ([l.output_shape for l in layers]))
 
         self.mode = mode
         self.concat_axis = concat_axis
@@ -349,14 +360,17 @@ class Merge(Layer):
         elif self.mode == 'dot':
             shape1 = list(input_shapes[0])
             shape2 = list(input_shapes[1])
-            for i in self.dot_axes[0]:
-                shape1.pop(i)
-            for i in self.dot_axes[1]:
-                shape2.pop(i)
-            shape = shape1 + shape2[1:]
-            if len(shape) == 1:
-                shape.append(1)
-            return tuple(shape)
+            dot_axes = []
+            for axes in self.dot_axes:
+                dot_axes.append([index-1 for index in axes])
+            tensordot_output = np.tensordot(np.zeros(tuple(shape1[1:])),
+                                            np.zeros(tuple(shape2[1:])),
+                                            axes=dot_axes)
+            if len(tensordot_output.shape) == 0:
+                shape = (1,)
+            else:
+                shape = tensordot_output.shape
+            return (shape1[0],) + shape
         elif self.mode == 'cos':
             return tuple(input_shapes[0][0], 1)
 
@@ -392,13 +406,13 @@ class Merge(Layer):
             l1 = self.layers[0].get_output(train)
             l2 = self.layers[1].get_output(train)
             output = T.batched_tensordot(l1, l2, self.dot_axes)
-            output = output.dimshuffle((0, 'x'))
             return output
         elif self.mode == 'cos':
             l1 = self.layers[0].get_output(train)
             l2 = self.layers[1].get_output(train)
-            output, _ = theano.scan(lambda v1, v2: T.dot(v1, v2)/T.sqrt(T.dot(v1, v1) * T.dot(v2, v2)), sequences=[l1, l2], outputs_info=None)
-            output = output.dimshuffle((0, 'x'))
+            output, _ = theano.scan(lambda v1, v2: T.dot(v1, v2) / T.sqrt(T.dot(v1, v1) * T.dot(v2, v2)),
+                                    sequences=[l1, l2],
+                                    outputs_info=None)
             return output
         else:
             raise Exception('Unknown merge mode')
@@ -446,7 +460,6 @@ class Merge(Layer):
         return dict(list(base_config.items()) + list(config.items()))
 
 
-
 class Dropout(MaskedLayer):
     '''
         Hinton's dropout.
diff --git a/tests/auto/test_sequential_model.py b/tests/auto/test_sequential_model.py
index 270ce15ac..db76ddf23 100644
--- a/tests/auto/test_sequential_model.py
+++ b/tests/auto/test_sequential_model.py
@@ -128,7 +128,7 @@ class TestSequential(unittest.TestCase):
         nloss = model.evaluate([X_train, X_train], y_train, verbose=0)
         print(nloss)
         assert(loss == nloss)
-        
+
     def test_merge_dot1(self):
         print('Test merge: dot')
         left = Sequential()
@@ -146,7 +146,7 @@ class TestSequential(unittest.TestCase):
         model.add(Activation('softmax'))
 
         model.compile(loss='categorical_crossentropy', optimizer='rmsprop')
-        
+
     def test_merge_dot2(self):
         print('Test merge: dot')
         left = Sequential()
@@ -158,12 +158,13 @@ class TestSequential(unittest.TestCase):
         right.add(Activation('relu'))
 
         model = Sequential()
-        model.add(Merge([left, right], mode='dot', dot_axes=([1],[1])))
+        model.add(Merge([left, right], mode='dot', dot_axes=([1], [1])))
 
         model.add(Dense(nb_class))
         model.add(Activation('softmax'))
 
         model.compile(loss='categorical_crossentropy', optimizer='rmsprop')
+
     def test_merge_concat(self):
         print('Test merge: concat')
         left = Sequential()