crossposted from my blog There are two ways we miscalibrate risk. We risk too much on things that are low conviction We risk too little on things that are high conviction I learned these lessons in poker and in trading and they have helped me reason about broader life. I call them the fold pre […]

[Submitted on 27 Jun 2025] View a PDF of the paper titled Visual Structures Helps Visual Reasoning: Addressing the Binding Problem in VLMs, by Amirmohammad Izadi and 6 other authors View PDF HTML (experimental) Abstract:Despite progress in Vision-Language Models (VLMs), their capacity for visual reasoning is often limited by the \textit{binding problem}: the failure to

arXiv:2506.22419v1 Announce Type: cross Abstract: Rapid advancements in large language models (LLMs) have the potential to assist in scientific progress. A critical capability toward this endeavor is the ability to reproduce existing work. To evaluate the ability of AI agents to reproduce results in an active research area, we introduce the Automated LLM Speedrunning Benchmark,

[Submitted on 27 Jun 2025] View a PDF of the paper titled QuKAN: A Quantum Circuit Born Machine approach to Quantum Kolmogorov Arnold Networks, by Yannick Werner and 6 other authors View PDF HTML (experimental) Abstract:Kolmogorov Arnold Networks (KANs), built upon the Kolmogorov Arnold representation theorem (KAR), have demonstrated promising capabilities in expressing complex functions

arXiv:2506.22385v1 Announce Type: cross Abstract: Video Large Multimodal Models (VLMMs) have made impressive strides in understanding video content, but they often struggle with abstract and adaptive reasoning-the ability to revise their interpretations when new information emerges. In reality, conclusions are rarely set in stone; additional context can strengthen or weaken an initial inference. To address

arXiv:2506.22331v1 Announce Type: cross Abstract: Greedy Equivalence Search (GES) is a classic score-based algorithm for causal discovery from observational data. In the sample limit, it recovers the Markov equivalence class of graphs that describe the data. Still, it faces two challenges in practice: computational cost and finite-sample accuracy. In this paper, we develop Less Greedy

arXiv:2506.21990v1 Announce Type: cross Abstract: The developments in transformer encoder-decoder architectures have led to significant breakthroughs in machine translation, Automatic Speech Recognition (ASR), and instruction-based chat machines, among other applications. The pre-trained models were trained on vast amounts of generic data over a few epochs (fewer than five in most cases), resulting in their strong

[Submitted on 4 Mar 2024 (v1), last revised 27 Jun 2025 (this version, v2)] View a PDF of the paper titled Enhancing Object Detection Robustness: Detecting and Restoring Confidence in the Presence of Adversarial Patch Attacks, by Roie Kazoom and 1 other authors View PDF HTML (experimental) Abstract:The widespread adoption of computer vision systems has

arXiv:2506.21839v1 Announce Type: cross Abstract: We challenge text-to-image models with generating escape room puzzle images that are visually appealing, logically solid, and intellectually stimulating. While base image models struggle with spatial relationships and affordance reasoning, we propose a hierarchical multi-agent framework that decomposes this task into structured stages: functional design, symbolic scene graph reasoning, layout

…and you will tell them the story of how once you found the Artifact that gave you mastery of the universe, and you refused to take more than about three minutes figuring out what to use it for, because that would have been annoying. ~Scott Alexander, “In The Balance” Disclaimer: The current version of this