Tootfinder

Breaking Universality in the Lower Order Terms in the 1-level and 2-level Density of Holomorphic Cusp Newforms
Lawrence Dillon, Xiaoyao Huang, Say-Yeon Kwon, Meiling Laurence, Steven J. Miller, Vishal Muthuvel, Luke Rowen, Pramana Saldin, Steven Zanetti
https://arxiv.org/abs/2508.21691

Breaking Universality in the Lower Order Terms in the 1-level and 2-level Density of Holomorphic Cusp Newforms
The Katz-Sarnak density conjecture states that, as the analytic conductor $R \to \infty$, the distribution of the normalized low-lying zeros (those near the central point $s = 1/2$) converges to the scaling limits of eigenvalues clustered near 1 of subgroups of $U(N)$. There is extensive evidence supporting this conjecture for many families, including the family of holomorphic cusp newforms. Interestingly, there are very few choices for the main term of the limiting behavior. In 2009, S. J. Mil…

reminded that in langford’s story BLIT the basilisk image came from anti-AI research and the concept of “Gödelian shock input”

Metric Poincar\'e inequalities for graphs
Dylan J. Altschuler, Pandelis Dodos, Konstantin Tikhomirov, Konstantinos Tyros
https://arxiv.org/abs/2509.25489 https://

Metric Poincaré inequalities for graphs
This article considers embeddings of bounded degree graphs into general metric spaces. Our first main result is a metric analogue of Matoušek's extrapolation that relates the Poincaré constants $γ(G,\varrho^p)$ and $γ(G,\varrho^q)$ for any pair of exponents $0 < p,q < \infty$, any bounded degree expander graph $G$, and any metric space $\mathcal{M}=(M,\varrho)$. Our second main result provides a sharp estimate of the Poincaré constant $γ(G,\varrho)$ in terms of the cardinalities of the ve…

We have a slate of jobs opening up - apologies, only have a LinkedIn link for now: https://www.linkedin.com/posts/delyno-dutoit_city-of-cape-town-jobs-linkedin-activity-7361684604451221504-hJb1
Will update and do a lon…

New positions in the City of Cape Town Data Analytics Hub! | Delyno du Toit
New positions in the City of Cape Town Data Analytics Hub! The Hub is the next chapter for our highly successful Data Science team, expanding its mission to be the nerve center for data-driven strategy and innovation across our entire organization. What if your next data product could help manage a City's water supply or your models make public transport more efficient? We are looking for curious and talented individuals to join us. We have several open positions: -) Head: Data Science -) H…

MCTR: Midpoint Corrected Triangulation for Autonomous Racing via Digital Twin Simulation in CARLA
Junhao Ye, Cheng Hu, Yiqin Wang, Weizhan Huang, Nicolas Baumann, Jie He, Meixun Qu, Lei Xie, Hongye Su
https://arxiv.org/abs/2508.12729

MCTR: Midpoint Corrected Triangulation for Autonomous Racing via Digital Twin Simulation in CARLA
In autonomous racing, reactive controllers eliminate the computational burden of the full See-Think-Act autonomy stack by directly mapping sensor inputs to control actions. This bypasses the need for explicit localization and trajectory planning. A widely adopted baseline in this category is the Follow-The-Gap method, which performs trajectory planning using LiDAR data. Building on FTG, the Delaunay Triangulation-based Racing algorithm introduces further enhancements. However, DTR's use of circ…

Replaced article(s) found for econ.TH. https://arxiv.org/list/econ.TH/new
[1/1]:
- Diffusion in dynamic networks with time-varying inputs to allocate responsibility
Rosa van den Ende, Dylan Laplace Mermoud

Scalable In-context Ranking with Generative Models
Nilesh Gupta, Chong You, Srinadh Bhojanapalli, Sanjiv Kumar, Inderjit Dhillon, Felix Yu
https://arxiv.org/abs/2510.05396 https…

Scalable In-context Ranking with Generative Models
In-context Ranking (ICR) is an emerging paradigm for Information Retrieval (IR), which leverages contextual understanding of LLMs by directly incorporating the task description, candidate documents, and the query into the model's input prompt and tasking the LLM to identify relevant document(s). While it is effective, efficiency is a significant challenge in this paradigm, especially as the candidate list grows due to quadratic/super-linear scaling of attention operation with context length. To…

Towards Balanced Behavior Cloning from Imbalanced Datasets
Sagar Parekh, Heramb Nemlekar, Dylan P. Losey
https://arxiv.org/abs/2508.06319 https://arxiv.org…

Towards Balanced Behavior Cloning from Imbalanced Datasets
Robots should be able to learn complex behaviors from human demonstrations. In practice, these human-provided datasets are inevitably imbalanced: i.e., the human demonstrates some subtasks more frequently than others. State-of-the-art methods default to treating each element of the human's dataset as equally important. So if -- for instance -- the majority of the human's data focuses on reaching a goal, and only a few state-action pairs move to avoid an obstacle, the learning algorithm will pla…

Dylan's Late Styles
https://ift.tt/3JrkZLQ
updated: Tuesday, October 7, 2025 - 12:36pmfull name / name of organization: Brady…
via Input 4 RELCFP https://ift.tt/mI2…

Dylan's Late Styles
https://ift.tt/3JrkZLQ
updated: Tuesday, October 7, 2025 - 12:36pmfull name / name of organization: Brady…
via Input 4 RELCFP https://ift.tt/mI2…