diff --git a/submission_rules.adoc b/submission_rules.adoc
index b485d40..aeb0e25 100644
--- a/submission_rules.adoc
+++ b/submission_rules.adoc
@@ -327,10 +327,9 @@ System names and implementation names may be arbitrary.
 
 Here is the list of mandatory files for all submissions in any division/category. However, your submission should still include all software information and related information for results replication. 
 
-
 *   mlperf_log_summary.txt
 *   mlperf_log_detail.txt
-*   Mlperf_log_accuracy.json [ TODO: handle differently in v0.6?]
+*   mlperf_log_accuracy.json
 *   user.conf
 *   calibration or weight transformation related code if the original MLPerf models are not used
 *   actual models if the models are not deterministically generated
@@ -340,6 +339,16 @@ Here is the list of mandatory files for all submissions in any division/category
 *   <system_desc_id>.json
 *   compliance_checker_log.txt
 
+For some models mlperf_log_accuracy.json can get very large. Because of this we truncate mlperf_log_accuracy.log in submissions
+using a tool.
+A submiter will run the tool before submitting to mlperf and ***keep*** the original mlperf_log_accuracy.log files inside their organization.
+The original files might be requested by mlperf during submission review so you need to store them.
+Run the tool as follows, assuming <SOURCE> is your local subumission tree and <DEST> the location of the github submission repo:
+
+```
+# from top of the inference source tree
+python3 tools/submission/truncate_accuracy_log.py --input <SOURCE> --output <DEST>
+```
 
 ### <system_desc_id>.json metadata
 
@@ -471,7 +480,7 @@ This section in progress [TODO].
 
 #### Inference
 
-Refer to the documentation found under https://github.com/mlperf/inference/tree/master/v0.7/compliance/nvidia
+Refer to the documentation found under https://github.com/mlperf/inference/tree/master/compliance/nvidia
 
 
 ## Review