docs: remove references to closed and fixed issues from compatibility guide

docs/source/user-guide/latest/compatibility/expressions/_category_template/cast.md

@@ -34,8 +34,6 @@ Cast operations in Comet fall into three levels of support:
 
 Cast will fall back to Spark in some cases when ANSI mode is enabled. This can be enabled by setting `spark.comet.expression.Cast.allowIncompatible=true`. See the [Comet Supported Expressions Guide](../../../expressions.md) for more information on this configuration setting.
 
-There is an [epic](https://github.com/apache/datafusion-comet/issues/313) where we are tracking the work to fully implement ANSI support.
-
 ## String to Decimal
 
 Comet's native `CAST(string AS DECIMAL)` implementation matches Apache Spark's behavior,
@@ -160,5 +158,3 @@ as `"1.23E+4"`).
 
 <!--BEGIN:CAST_ANSI_TABLE-->
 <!--END:CAST_ANSI_TABLE-->
-
-See the [tracking issue](https://github.com/apache/datafusion-comet/issues/286) for more details.

docs/source/user-guide/latest/compatibility/expressions/_category_template/datetime.md

@@ -19,16 +19,12 @@ under the License.
 
 # Date/Time Expressions
 
-- **Hour, Minute, Second**: Incorrectly apply timezone conversion to TimestampNTZ inputs. TimestampNTZ stores local
-  time without timezone, so no conversion should be applied. These expressions work correctly with Timestamp inputs.
-  [#3180](https://github.com/apache/datafusion-comet/issues/3180)
 - **TruncTimestamp (date_trunc)**: In non-UTC sessions the native path is marked Incompatible and
   routes through the JVM codegen dispatcher by default, producing Spark-identical results. The
   native path is itself correct for dates within chrono-tz's DST horizon (approximately year 2100;
   see "Date and Time Functions" below) and can be enabled by setting
   `spark.comet.expression.TruncTimestamp.allowIncompatible=true`. TimestampNTZ inputs are handled
   correctly regardless of session timezone (timezone-independent truncation).
-  [#2649](https://github.com/apache/datafusion-comet/issues/2649)
 
 ## Date and Time Functions
 

docs/source/user-guide/latest/compatibility/operators.md

@@ -44,7 +44,7 @@ incorrect result. When any single window expression in a `WindowExec` falls back
   and `sum` / `avg` on year-month or day-time interval input types. Windowed aggregates inherit the same input-type
   support as the batch aggregates, so these fall back in both contexts.
 - `sum` or `avg` on `DECIMAL` with a sliding (non ever-expanding) frame, because the sliding path would wrap on
-  overflow instead of returning Spark's `NULL` ([#4729](https://github.com/apache/datafusion-comet/issues/4729)).
+  overflow instead of returning Spark's `NULL`.
 - `RANGE` frame with an explicit offset when the `ORDER BY` column is `DATE` or `DECIMAL`
   ([#4834](https://github.com/apache/datafusion-comet/issues/4834)).
 - `first_value` / `last_value` on a `RANGE` frame with a literal offset

docs/source/user-guide/latest/compatibility/scans.md

@@ -43,15 +43,11 @@ The following features are not supported and cause Comet to fall back to Spark:
 - No support for `input_file_name()`, `input_file_block_start()`, or `input_file_block_length()` SQL functions.
   Comet's Parquet scan does not use Spark's `FileScanRDD`, so these functions cannot populate their values.
 - No support for `ignoreMissingFiles` or `ignoreCorruptFiles` being set to `true`
-- Duplicate field names in case-insensitive mode (e.g., a Parquet file with both `B` and `b` columns)
-  are detected at read time and raise a `SparkRuntimeException` with error class `_LEGACY_ERROR_TEMP_2093`,
-  matching Spark's behavior.
 - `spark.sql.parquet.enableVectorizedReader=false`. Disabling the vectorized reader opts into
   Spark's parquet-mr semantics (silent overflow, null-on-narrowing), which Comet's native reader
   does not replicate. By default Comet falls back to Spark in this case. Set
   `spark.comet.scan.allowDisabledParquetVectorizedReader=true` to opt in to running the
-  Comet Parquet scan regardless. See
-  [#4352](https://github.com/apache/datafusion-comet/issues/4352).
+  Comet Parquet scan regardless.
 
 The following limitation may produce incorrect results without falling back to Spark:
 
@@ -68,13 +64,6 @@ The following limitations raise an error at scan time rather than falling back t
   non-UTF-8 bytes fails with `Parquet error: encountered non UTF-8 data`. Disable Comet for the
   query, or cast the column to `BINARY` before persisting, if you need to preserve non-UTF-8 bytes.
   See [#4121](https://github.com/apache/datafusion-comet/issues/4121).
-- Reading `TimestampLTZ` as `TimestampNTZ` on Spark 3.x. Spark raises an error per
-  [SPARK-36182](https://issues.apache.org/jira/browse/SPARK-36182) because LTZ encodes UTC-adjusted
-  instants that cannot be safely reinterpreted as timezone-free values, and Comet matches this by
-  rejecting the read. This applies to all LTZ physical encodings (INT96, TIMESTAMP_MICROS,
-  TIMESTAMP_MILLIS). On Spark 4.0+, this read is permitted
-  ([SPARK-47447](https://issues.apache.org/jira/browse/SPARK-47447)) and Comet matches Spark's
-  behavior. See [#4219](https://github.com/apache/datafusion-comet/issues/4219).
 
 ### Schema Mismatch Handling
 

docs/source/user-guide/latest/compatibility/spark-versions.md

@@ -60,8 +60,7 @@ Spark 4.0.2 is supported with Java 17 and Scala 2.13.
 
 ### Known Limitations
 
-- **Collation support** ([#1947](https://github.com/apache/datafusion-comet/issues/1947),
-  [#4051](https://github.com/apache/datafusion-comet/issues/4051)): Spark 4.0 introduced collation
+- **Collation support**: Spark 4.0 introduced collation
   support. Non-default collated strings are not yet supported by Comet and will fall back to Spark.
 
 ## Spark 4.1