diff --git a/CHANGELOG.md b/CHANGELOG.md
index 63cd9ba5c..ad2da0d5f 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -55,7 +55,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/)
 
 ### New Features and Optimizations
 - Implement Kahneman-Tversky Optimization (KTO).
-- Sequence packing is now supported when running SFT with SFTChatDataset.
+- Sequence packing is now supported when running SFT with prompt-response datasets.
 
 ### Breaking Changes
 
@@ -75,7 +75,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/)
 - Critic and Reward Model server refactored. Now the reward model will have a flag called `model.forward_micro_batch_size` which determines the micro batch size on which it runs inferences. This can be higher than the training micro batch size since during inference, we have less memory pressure.
 - In the critic and reward model server, it is now possible to specify `inference_micro_batch_size` as a list.  This allows us to provide more information to PyTriton regarding the preferred batch sizes for inference.
 - It is no longer a requirement to specify `num_rollout_samples` to be a multiple of `inference_micro_batch_size * dp size` in PPO.
-- Sequence packing is now supported when running SFT with SFTChatDataset.
+- Sequence packing is now supported when running SFT with prompt-response datasets.
 - Add online rejection sampling algorithm.
 
 ### Breaking Changes