diff --git a/vowpalwabbit/core/src/reductions/eigen_memory_tree.cc b/vowpalwabbit/core/src/reductions/eigen_memory_tree.cc
index 37c856644fa..11da7bbb24b 100644
--- a/vowpalwabbit/core/src/reductions/eigen_memory_tree.cc
+++ b/vowpalwabbit/core/src/reductions/eigen_memory_tree.cc
@@ -489,15 +489,7 @@ void tree_bound(emt_tree& b, emt_example* ec)
   }
 }
 
-void scorer_features(const emt_feats& f1, VW::features& out)
-{
-  for (auto p : f1)
-  {
-    if (p.second != 0) { out.push_back(p.second, p.first); }
-  }
-}
-
-void scorer_features(const emt_feats& f1, const emt_feats& f2, VW::features& out)
+void scorer_features_sub(const emt_feats& f1, const emt_feats& f2, VW::features& out)
 {
   auto iter1 = f1.begin();
   auto iter2 = f2.begin();
@@ -535,15 +527,31 @@ void scorer_features(const emt_feats& f1, const emt_feats& f2, VW::features& out
   }
 }
 
+void scorer_features_mul(const emt_feats& f1, const emt_feats& f2, VW::features& out)
+{
+  auto iter1 = f1.begin();
+  auto iter2 = f2.begin();
+
+  while (iter1 != f1.end() && iter2 != f2.end())
+  {
+    if (iter1->first < iter2->first) { iter1++; }
+    else if (iter2->first < iter1->first) { iter2++; }
+    else
+    {
+      out.push_back(iter1->second * iter2->second, iter1->first);
+      iter1++;
+      iter2++;
+    }
+  }
+}
+
 void scorer_example(emt_tree& b, const emt_example& ex1, const emt_example& ex2)
 {
   VW::example& out = *b.ex;
 
   static constexpr VW::namespace_index X_NS = 'x';
-  static constexpr VW::namespace_index Z_NS = 'z';
 
   out.feature_space[X_NS].clear();
-  out.feature_space[Z_NS].clear();
 
   if (b.scorer_type == emt_scorer_type::SELF_CONSISTENT_RANK)
   {
@@ -552,7 +560,7 @@ void scorer_example(emt_tree& b, const emt_example& ex1, const emt_example& ex2)
 
     out.interactions->clear();
 
-    scorer_features(ex1.full, ex2.full, out.feature_space[X_NS]);
+    scorer_features_sub(ex1.full, ex2.full, out.feature_space[X_NS]);
 
     out.total_sum_feat_sq = out.feature_space[X_NS].sum_feat_sq;
     out.num_features = out.feature_space[X_NS].size();
@@ -565,26 +573,13 @@ void scorer_example(emt_tree& b, const emt_example& ex1, const emt_example& ex2)
   {
     out.indices.clear();
     out.indices.push_back(X_NS);
-    out.indices.push_back(Z_NS);
 
     out.interactions->clear();
-    out.interactions->push_back({X_NS, Z_NS});
 
-    b.all->feature_tweaks_config.ignore_some_linear = true;
-    b.all->feature_tweaks_config.ignore_linear[X_NS] = true;
-    b.all->feature_tweaks_config.ignore_linear[Z_NS] = true;
+    scorer_features_mul(ex1.full, ex2.full, out.feature_space[X_NS]);
 
-    scorer_features(ex1.full, out.feature_space[X_NS]);
-    scorer_features(ex2.full, out.feature_space[Z_NS]);
-
-    // when we receive ex1 and ex2 their features are indexed on top of eachother. In order
-    // to make sure VW recognizes the features from the two examples as separate features
-    // we apply a map of multiplying by 2 and then offseting by 1 on the second example.
-    for (auto& j : out.feature_space[X_NS].indices) { j = j * 2; }
-    for (auto& j : out.feature_space[Z_NS].indices) { j = j * 2 + 1; }
-
-    out.total_sum_feat_sq = out.feature_space[X_NS].sum_feat_sq + out.feature_space[Z_NS].sum_feat_sq;
-    out.num_features = out.feature_space[X_NS].size() + out.feature_space[Z_NS].size();
+    out.total_sum_feat_sq = out.feature_space[X_NS].sum_feat_sq;
+    out.num_features = out.feature_space[X_NS].size();
 
     auto initial = emt_initial(b.initial_type, ex1.full, ex2.full);
     out.ex_reduction_features.get<VW::simple_label_reduction_features>().initial = initial;
@@ -741,13 +736,14 @@ void node_split(emt_tree& b, emt_node& cn)
   cn.examples.clear();
 }
 
-void node_insert(emt_node& cn, std::unique_ptr<emt_example> ex)
+void node_insert(emt_tree& b, emt_node& cn, std::unique_ptr<emt_example> ex)
 {
   for (auto& cn_ex : cn.examples)
   {
     if (cn_ex->full == ex->full) { return; }
   }
   cn.examples.push_back(std::move(ex));
+  tree_bound(b, cn.examples.back().get());
 }
 
 emt_example* node_pick(emt_tree& b, learner& base, emt_node& cn, const emt_example& ex)
@@ -779,16 +775,15 @@ void node_predict(emt_tree& b, learner& base, emt_node& cn, emt_example& ex, VW:
   auto* closest_ex = node_pick(b, base, cn, ex);
   ec.pred.multiclass = (closest_ex != nullptr) ? closest_ex->label : 0;
   ec.loss = (ec.l.multi.label != ec.pred.multiclass) ? ec.weight : 0;
+  if (closest_ex != nullptr) { tree_bound(b, closest_ex); }
 }
 
 void emt_predict(emt_tree& b, learner& base, VW::example& ec)
 {
   b.all->feature_tweaks_config.ignore_some_linear = false;
   emt_example ex(*b.all, &ec);
-
   emt_node& cn = *tree_route(b, ex);
   node_predict(b, base, cn, ex, ec);
-  tree_bound(b, &ex);
 }
 
 void emt_learn(emt_tree& b, learner& base, VW::example& ec)
@@ -797,10 +792,9 @@ void emt_learn(emt_tree& b, learner& base, VW::example& ec)
   auto ex = VW::make_unique<emt_example>(*b.all, &ec);
 
   emt_node& cn = *tree_route(b, *ex);
-  scorer_learn(b, base, cn, *ex, ec.weight);
   node_predict(b, base, cn, *ex, ec);  // vw learners predict and emt_learn
-  tree_bound(b, ex.get());
-  node_insert(cn, std::move(ex));
+  scorer_learn(b, base, cn, *ex, ec.weight);
+  node_insert(b, cn, std::move(ex));
   node_split(b, cn);
 }
 
diff --git a/vowpalwabbit/core/tests/eigen_memory_tree_test.cc b/vowpalwabbit/core/tests/eigen_memory_tree_test.cc
index 82624c846df..da9aeafc0cc 100644
--- a/vowpalwabbit/core/tests/eigen_memory_tree_test.cc
+++ b/vowpalwabbit/core/tests/eigen_memory_tree_test.cc
@@ -131,7 +131,7 @@ TEST(EigenMemoryTree, ExactMatchWithRouterTest)
   }
 }
 
-TEST(EigenMemoryTree, Bounding)
+TEST(EigenMemoryTree, BoundingDrop)
 {
   auto vw = VW::initialize(vwtest::make_args("--quiet", "--emt", "--emt_tree", "5"));
   auto* tree = get_emt_tree(*vw);
@@ -148,6 +148,45 @@ TEST(EigenMemoryTree, Bounding)
   EXPECT_EQ(tree->root->router_weights.size(), 0);
 }
 
+TEST(EigenMemoryTree, BoundingPredict)
+{
+  auto vw = VW::initialize(vwtest::make_args("--quiet", "--emt", "--emt_tree", "3"));
+  auto* tree = get_emt_tree(*vw);
+
+  auto* ex = VW::read_example(*vw, "1 | 1");
+  vw->predict(*ex);
+  vw->finish_example(*ex);
+
+  EXPECT_EQ(tree->bounder->list.size(), 0);
+}
+
+TEST(EigenMemoryTree, BoundingRecency)
+{
+  auto vw = VW::initialize(vwtest::make_args("--quiet", "--emt", "--emt_tree", "3"));
+  auto* tree = get_emt_tree(*vw);
+
+  for (int i = 0; i < 3; i++)
+  {
+    auto* ex = VW::read_example(*vw, std::to_string(i) + " | " + std::to_string(i));
+    vw->learn(*ex);
+    vw->finish_example(*ex);
+  }
+
+  EXPECT_EQ((*tree->bounder->list.begin())->base[0].first, 2);
+
+  auto* ex1 = VW::read_example(*vw, "1 | 1");
+  vw->predict(*ex1);
+  vw->finish_example(*ex1);
+
+  EXPECT_EQ((*tree->bounder->list.begin())->base[0].first, 1);
+
+  auto* ex2 = VW::read_example(*vw, "1 | 0");
+  vw->predict(*ex2);
+  vw->finish_example(*ex2);
+
+  EXPECT_EQ((*tree->bounder->list.begin())->base[0].first, 0);
+}
+
 TEST(EigenMemoryTree, Split)
 {
   auto args = vwtest::make_args("--quiet", "--emt", "--emt_tree", "10", "--emt_leaf", "3");