ReFeed: Multi-dimensional Summarization Refinement with Reflective
  Reasoning on Feedback
Summarization refinement faces challenges when extending to multi-dimension.
In this paper, we introduce ReFeed, a powerful summarization refinement
pipeline that enhances multiple dimensions through reflective reasoning on
feedback. To achieve this, we release SumFeed-CoT, a large-scale Long-CoT-based
dataset optimized for training a lightweight model with reflective reasoning.
Our experiments reveal how the number of dimensions, feedback exposure, and
reasoning policy influence refinement performance, highlighting reflective
reasoning and simultaneously addressing multiple feedback is crucial to
mitigate trade-off between dimensions. Furthermore, ReFeed is robust to noisy
feedback and feedback order. Lastly, our finding emphasizes that creating data
with a proper goal and guideline constitutes a fundamental pillar of effective
reasoning. The dataset and model will be released.
67e623f10aaa5e9f7cf8a179
Taewon Yun
claimed_verified
2025-03-28T08:36:56.604Z
65642d7401de72cb63165d22
/avatars/1f4417c4ac5e781ce73eae1060e3f7f2.svg
ytaewon
user
hamzzi
67e623f10aaa5e9f7cf8a17a
Jihwan Oh
67e623f10aaa5e9f7cf8a17b
Hyangsuk Min
admin_assigned
2025-03-31T10:01:07.989Z
6510c8ebf26dbb8827ee5e80
/avatars/cc49a2f176c951007006e0dae331bc50.svg
Hyangsuk Min
user
hyang0503
67e623f10aaa5e9f7cf8a17c
Yuho Lee
admin_assigned
2025-03-31T10:01:13.949Z
63f6eec4c96958470d207698
/avatars/7fba5e561b809a1623bf2228435f1aad.svg
Yuho Lee
user
Myyhlee
67e623f10aaa5e9f7cf8a17d
Jihwan Bang
admin_assigned
2025-03-31T10:01:20.117Z
644938d43def32791088b762
/avatars/1f17916b92ef13452151175cb8cafdf9.svg
Jihwan Bang
user
hwany-j
67e623f10aaa5e9f7cf8a17e
Jason Cai
admin_assigned
2025-03-31T10:01:43.066Z
6463c26aa5af935cfe70f08d
/avatars/33b1210098891db54f57d1344b5110fb.svg
Jinglun (Jason) Cai
user
jasoncai
67e623f10aaa5e9f7cf8a17f
Hwanjun Song
ReFeed: Multi-dimensional Summarization Refinement with Reflective
  Reasoning on Feedback
Summarization refinement faces challenges when extending to multi-dimension.
In this paper, we introduce ReFeed, a powerful summarization refinement
pipeline that enhances multiple dimensions through reflective reasoning on
feedback. To achieve this, we release SumFeed-CoT, a large-scale Long-CoT-based
dataset optimized for training a lightweight model with reflective reasoning.
Our experiments reveal how the number of dimensions, feedback exposure, and
reasoning policy influence refinement performance, highlighting reflective
reasoning and simultaneously addressing multiple feedback is crucial to
mitigate trade-off between dimensions. Furthermore, ReFeed is robust to noisy
feedback and feedback order. Lastly, our finding emphasizes that creating data
with a proper goal and guideline constitutes a fundamental pillar of effective
reasoning. The dataset and model will be released.
Long-CoT-based dataset reflective reasoning refinement performance ReFeed SumFeed-CoT