Paper Rebuttal

• Rebuttal by Authors

• Official Comment by Authors

• peer pressure

• small table

• followup reminder
• We have addressed all reviewer concerns and added new experiments that further validate our conclusions.

Dear Reviewer,
We have addressed all reviewer concerns and added new experiments that further validate our conclusions. If everything is resolved, we would appreciate your consideration of a score update.

Dear Reviewer,

Having addressed your concerns, we would appreciate your feedback during this discussion period. Let us know if there are any further questions that we can clarify, otherwise, we would appreciate it if you would consider increasing your score.

Thanks!

Dear Reviewer,

As the discussion period deadline approaches, we would appreciate your feedback on our previous response. Thanks for your active engagement in the review process.

I encourage the AC to disregard this review during final reviews.
While some of this is reasonable, a request for a ~ indicates that this review was either AI generated or the reviewer is not well read enough in this field (or perhaps insufficiency skilled) to be making the review in the first place.

Scaling In-the-Wild Training for Diffusion-based Illumination...

Diffusion-based image generators are becoming unique methods for illumination harmonization and editing. The current bottleneck in scaling up the training of diffusion-based illumination editing...

https://openreview.net/forum?id=u1cQYxRI1H

Simplifying, Stabilizing and Scaling Continuous-time Consistency...

Consistency models (CMs) are a powerful class of diffusion-based generative models optimized for fast sampling. Most existing CMs are trained using discretized timesteps, which introduce additional...

https://openreview.net/forum?id=LyJi5ugyJx

Special Unitary Parameterized Estimators of Rotation

This paper revisits the topic of rotation estimation through the lens of special unitary matrices. We begin by reformulating Wahba’s problem using $SU(2)$ to derive multiple solutions that yield...

https://openreview.net/forum?id=VaS6xcDrTb

examples

Quantifying Elicitation of Latent Capabilities in Language Models

Large language models often possess latent capabilities that lie dormant unless explicitly elicited, or surfaced, through fine-tuning or prompt engineering. Predicting, assessing, and understanding...

https://openreview.net/forum?id=Dkgx2pS4Ww

Open Problems in Mechanistic Interpretability

Mechanistic interpretability aims to understand the computational mechanisms underlying neural networks' capabilities in order to accomplish concrete scientific and engineering goals. Progress in...

https://openreview.net/forum?id=91H76m9Z94

MaxInfoRL: Boosting exploration in reinforcement learning through...

Reinforcement learning (RL) algorithms aim to balance exploiting the current best strategy with exploring new options that could lead to higher rewards. Most common RL algorithms use undirected...

https://openreview.net/forum?id=R4q3cY3kQf