Tootfinder

$F$-injectivity does not imply $F$-fullness in normal domains
Alessandro De Stefani, Thomas Polstra, Austyn Simpson
https://arxiv.org/abs/2506.00646 https:…

$F$-injectivity does not imply $F$-fullness in normal domains
We construct examples of noetherian three-dimensional local geometrically normal domains of prime characteristic which are $F$-injective but not $F$-full. Along the way, we find examples of two-dimensional local geometrically normal domains which are $F$-injective but not $F$-anti-nilpotent. A crucial theme of our constructions is the behavior of $F$-injectivity along a purely inseparable finite base change.

SAMFusion: Sensor-Adaptive Multimodal Fusion for 3D Object Detection in Adverse Weather
Edoardo Palladin, Roland Dietze, Praveen Narayanan, Mario Bijelic, Felix Heide
https://arxiv.org/abs/2508.16408

SAMFusion: Sensor-Adaptive Multimodal Fusion for 3D Object Detection in Adverse Weather
Multimodal sensor fusion is an essential capability for autonomous robots, enabling object detection and decision-making in the presence of failing or uncertain inputs. While recent fusion methods excel in normal environmental conditions, these approaches fail in adverse weather, e.g., heavy fog, snow, or obstructions due to soiling. We introduce a novel multi-sensor fusion approach tailored to adverse weather conditions. In addition to fusing RGB and LiDAR sensors, which are employed in recent…

Just finished reading "Theory of Water" by Leanne Betasamosake Simpson. It's a departure from a lot of the other stuff I've read lately (mostly unchallenging fiction), but it's really great, and hits hard in this specific political moment. It's an Indigenous anarchist theory book, published this year, and unsurprisingly holds a lot of truths I found valuable to hear. Highly recommend it if you're feeling nihilistic.
#AmReading #Anarchist #Theory

The Snapshot Problem for the Euler-Poisson-Darboux Equation
Fulton Gonzalez, Jue Wang, Jens Christensen, Tomoyuki Kakehi
https://arxiv.org/abs/2507.13257 h…

The Snapshot Problem for the Euler-Poisson-Darboux Equation
The generalized Euler-Poisson-Darboux (EPD) equation with complex parameter $α$ is given by $$ Δ_x u=\frac{\partial^2 u}{\partial t^2}+\frac{n-1+2α}{t}\,\frac{\partial u}{\partial t}, $$ where $u(x,t)\in \mathscr E(\mathbb R^n\times \mathbb R)$, with $u$ even in $t$. For $α=0$ and $α=1$ the solution $u(x,t)$ represents a mean value over spheres and balls, respectively, of radius $|t|$ in $\mathbb R^n$. In this paper we consider existence and uniqueness results for the following t…

Symbiosis: Multi-Adapter Inference and Fine-Tuning
Saransh Gupta, Umesh Deshpande, Travis Janssen, Swami Sundararaman
https://arxiv.org/abs/2507.03220 http…

Symbiosis: Multi-Adapter Inference and Fine-Tuning
Parameter-efficient fine-tuning (PEFT) allows model builders to capture the task specific parameters into adapters, which are a fraction of the size of the original base model. Popularity of PEFT technique for fine-tuning has led to creation of a large number of adapters for popular Large Language Models (LLMs). However, existing frameworks fall short in supporting inference or fine-tuning with multiple adapters in the following ways. 1) For fine-tuning, each job needs to deploy its dedicated b…

Really feeling this right now, but it’s a LOT more than just 2.