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Notes on the 33-point Erdős--Szekeres Problem

Published:Dec 30, 2025 08:10
1 min read
ArXiv

Analysis

This paper addresses the open problem of determining ES(7) in the Erdős--Szekeres problem, a classic problem in computational geometry. It's significant because it tackles a specific, unsolved case of a well-known conjecture. The use of SAT encoding and constraint satisfaction techniques is a common approach for tackling combinatorial problems, and the paper's contribution lies in its specific encoding and the insights gained from its application to this particular problem. The reported runtime variability and heavy-tailed behavior highlight the computational challenges and potential areas for improvement in the encoding.
Reference

The framework yields UNSAT certificates for a collection of anchored subfamilies. We also report pronounced runtime variability across configurations, including heavy-tailed behavior that currently dominates the computational effort and motivates further encoding refinements.

Analysis

This paper introduces SC-Net, a novel network for two-view correspondence learning. It addresses limitations of existing CNN-based methods by incorporating spatial and cross-channel context. The proposed modules (AFR, BFA, PAR) aim to improve position-awareness, robustness, and motion field refinement, leading to better performance in relative pose estimation and outlier removal. The availability of source code is a positive aspect.
Reference

SC-Net outperforms state-of-the-art methods in relative pose estimation and outlier removal tasks on YFCC100M and SUN3D datasets.

Community#referral📝 BlogAnalyzed: Dec 28, 2025 16:00

Kling Referral Code Shared on Reddit

Published:Dec 28, 2025 15:36
1 min read
r/Bard

Analysis

This is a very brief post from Reddit's r/Bard subreddit sharing a referral code for "Kling." Without more context, it's difficult to assess the significance. It appears a user is simply sharing their referral code, likely to gain some benefit from others using it. The post is minimal and lacks any substantial information about Kling itself or the benefits of using the referral code. It's essentially a promotional post within a specific online community. The value of this information is limited to those already familiar with Kling and interested in using a referral code. It highlights the use of social media platforms for referral marketing within AI-related services or products.

Key Takeaways

Reference

Here is. The latest Kling referral code 7BFAWXQ96E65