diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
index 87500f0ca5149..68a83a55c8daa 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
@@ -1561,7 +1561,8 @@ object CollapseProject extends Rule[LogicalPlan] with AliasHelper {
    * Check if the given expression is cheap that we can inline it.
    */
   def isCheap(e: Expression): Boolean = e match {
-    case _: Attribute | _: OuterReference => true
+    // `BoundReference` is the codegen-bound form of an `Attribute`; a slot read, equally cheap.
+    case _: Attribute | _: OuterReference | _: BoundReference => true
     case _ if e.foldable => true
     // PythonUDF is handled by the rule ExtractPythonUDFs
     case _: PythonUDF =>
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/basicPhysicalOperators.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/basicPhysicalOperators.scala
index 88c74ab7adc41..3eadfe7b865e9 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/basicPhysicalOperators.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/basicPhysicalOperators.scala
@@ -31,6 +31,7 @@ import org.apache.spark.sql.catalyst.InternalRow
 import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.expressions.BindReferences.bindReferences
 import org.apache.spark.sql.catalyst.expressions.codegen._
+import org.apache.spark.sql.catalyst.optimizer.CollapseProject
 import org.apache.spark.sql.catalyst.plans.physical._
 import org.apache.spark.sql.execution.joins.{ShuffledHashJoinExec, SortMergeJoinExec}
 import org.apache.spark.sql.execution.metric.{SQLMetric, SQLMetrics}
@@ -316,12 +317,22 @@ case class FilterExec(condition: Expression, child: SparkPlan)
     // (e.g. decoding a decimal column for rows a cheaper earlier predicate would reject), so we
     // fall back to `generatePredicateCode`.
     //
+    // A *cheap* common subexpression does not count. `c BETWEEN lo AND hi` lowers to
+    // `c >= lo AND c <= hi`, so any `BETWEEN` (or a column referenced in several conjuncts) makes
+    // that column a common subexpression, but caching a cheap load saves nothing: the non-CSE path
+    // already loads each column lazily into a variable on demand. Taking the CSE path for it would
+    // only add the eager prologue that decodes every referenced column up front. Require a
+    // non-cheap common subexpression (per `CollapseProject.isCheap`) so filters like TPC-DS q28
+    // (`ss_quantity BETWEEN ... AND (ss_list_price BETWEEN ... OR ...)`, whose only repeats are the
+    // bare columns) keep the lazy, short-circuiting path.
+    //
     // `subexpressionElimination.filterExec.enabled` additionally gates this path so it can be
     // turned off independently of subexpression elimination elsewhere.
     val (prologueCode, predicateCode) =
       if (conf.subexpressionEliminationEnabled && conf.subexpressionEliminationFilterExecEnabled &&
           otherPreds.nonEmpty &&
-          otherPredsEquivalentExpressions.getCommonSubexpressions.nonEmpty) {
+          otherPredsEquivalentExpressions.getCommonSubexpressions
+            .exists(!CollapseProject.isCheap(_))) {
         // Pre-evaluate input variables before CSE analysis: CSE clears
         // ctx.currentVars[i].code as a side effect; without this pre-evaluation, Janino
         // fails when otherPreds reference the same input columns that CSE already
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/WholeStageCodegenSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/WholeStageCodegenSuite.scala
index 886df9184aca4..e013e59597f69 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/WholeStageCodegenSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/WholeStageCodegenSuite.scala
@@ -1225,6 +1225,48 @@ class WholeStageCodegenSuite extends SharedSparkSession
         "CSE-disabled codegen (i.e. fall back to the lazy, short-circuiting non-CSE path)")
   }
 
+  test("SPARK-56032: FilterExec skips CSE codegen when the only common subexpression is a leaf") {
+    // `c BETWEEN lo AND hi` lowers to `c >= lo AND c <= hi`, so a column used in a BETWEEN (or in
+    // several conjuncts) becomes a "common subexpression" -- but it is a bare leaf column whose
+    // load CSE cannot meaningfully cache, since the non-CSE path already loads columns lazily. The
+    // gate must not take the CSE path for it: doing so emits the eager prologue that decodes every
+    // referenced column (the decimals `p1`/`p2` here) up front, defeating the cheap `q` filter's
+    // short-circuiting. This is the TPC-DS q28 shape. Verify the leaf-only case falls back to the
+    // same code as CSE-disabled; `p1`/`p2` stand in for q28's decimal columns whose eager decode
+    // is the cost, though the fallback is type-independent.
+    val schema = StructType(Seq(
+      StructField("q", IntegerType, nullable = true),
+      StructField("p1", IntegerType, nullable = true),
+      StructField("p2", IntegerType, nullable = true)))
+    val data = spark.sparkContext.parallelize(Seq(
+      Row(4, 10, 7), Row(1, 10, 7), Row(null, 10, 7),
+      Row(5, 100, 7), Row(6, 100, 100), Row(3, 9, 1)))
+    val expected = Seq(Row(4, 10, 7), Row(5, 100, 7), Row(3, 9, 1))
+
+    def filterCode(cseEnabled: Boolean): String = {
+      withSQLConf(
+        SQLConf.SUBEXPRESSION_ELIMINATION_ENABLED.key -> cseEnabled.toString,
+        SQLConf.WHOLESTAGE_CODEGEN_ENABLED.key -> "true",
+        SQLConf.ADAPTIVE_EXECUTION_ENABLED.key -> "false") {
+        val df = spark.createDataFrame(data, schema)
+        // The only repeated expressions are the bare columns q, p1, p2 (each referenced by the two
+        // halves of its BETWEEN). No non-leaf expression is shared.
+        val filtered = df.where(
+          "q IS NOT NULL AND q BETWEEN 2 AND 6 AND (p1 BETWEEN 8 AND 18 OR p2 BETWEEN 5 AND 9)")
+        val plan = filtered.queryExecution.executedPlan
+        assert(plan.exists(_.isInstanceOf[WholeStageCodegenExec]),
+          "Filter should be in whole-stage codegen")
+        checkAnswer(filtered, expected)
+        codegenString(plan)
+      }
+    }
+
+    def normalize(code: String): String = code.replaceAll("#\\d+", "#")
+    assert(normalize(filterCode(cseEnabled = true)) == normalize(filterCode(cseEnabled = false)),
+      "With only leaf common subexpressions, CSE-enabled FilterExec codegen should be identical " +
+        "to CSE-disabled codegen (i.e. fall back to the lazy, short-circuiting non-CSE path)")
+  }
+
   test("SPARK-56032: subexpressionElimination.filterExec.enabled gates FilterExec CSE " +
     "independently of subexpression elimination") {
     // The conf disables CSE specifically for FilterExec while leaving subexpression elimination