4 citations · 13 across the 30 of their papers we have counts for
12 papers · 1 filter
AlphaDiana: A Measurement System for Agents in Verifiable Reasoning Tasks
Zhanke Zhou, Zongze Li, Weikai Huang +16
Agents pair reasoning models with harnesses that organize model calls, execute tools, load skill instructions, and retain history in memory. Understanding agent performance require…
LinearPFN: Amortized Variable Selection for Linear Models with Interactions
Louis Schiekiera, Max Zimmer, Christophe Roux +3
Spike-and-slab regression is a standard Bayesian formulation of variable selection: it returns a posterior distribution over which candidate effects are active rather than a single…
Optimal Gradient-Norm Minimization in Non-Euclidean Hölder-Smooth Convex Optimization
Nico Pelleriti, Maryam Shiran, David Martínez-Rubio +2
Minimizing gradients of a convex function is an important problem across optimization and learning tasks. The gradient provides a directly computable certificate of approximate sta…
Neural Field Tokenizations with Hierarchy and Spatial Locality Priors
Alonso Urbano, David W. Romero, Max Zimmer +1
Neural fields parameterize data as functions from coordinates to values, providing a unified framework for representation learning across modalities. Existing approaches are domina…
What Do Evolutionary Coding Agents Evolve?
Nico Pelleriti, Sree Harsha Nelaturu, Zhanke Zhou +4
Recent work pairs LLMs with evolutionary search to iteratively generate, modify, and select code using task-specific feedback. These systems have produced strong results in mathema…
Fast Isotopy Computation for T-Curves
Zoe Geiselmann, Michael Joswig, Lars Kastner +5
A T-curve of degree is given by a regular unimodular triangulation of together with a sign distribution on its lattice points. By Viro's Patchworking Theorem, thi…
The Agentic Researcher: A Practical Guide to AI-Assisted Research in Mathematics and Machine Learning
Max Zimmer, Nico Pelleriti, Christophe Roux +1
AI tools and agents are reshaping how researchers work, from proving theorems to training neural networks. Yet for many, it remains unclear how these tools fit into everyday resear…
ECHOSAT: Estimating Canopy Height Over Space And Time
Jan Pauls, Karsten Schrödter, Sven Ligensa +7
Forest monitoring is critical for climate change mitigation. However, existing global tree height maps provide only static snapshots and do not capture temporal forest dynamics, wh…
When Does Sparsity Mitigate the Curse of Depth in LLMs
Dilxat Muhtar, Xinyuan Song, Sebastian Pokutta +4
Recent work has demonstrated the curse of depth in large language models (LLMs), where later layers contribute less to learning and representation than earlier layers. Such under-u…
From Associations to Activations: Comparing Behavioral and Hidden-State Semantic Geometry in LLMs
Louis Schiekiera, Max Zimmer, Christophe Roux +2
We investigate the extent to which an LLM's hidden-state geometry can be recovered from its behavior in psycholinguistic experiments. Across eight instruction-tuned transformer mod…
Limits of combinatorial patchworking
Zoe Geiselmann, Michael Joswig, Lars Kastner +5
It is shown that there are real plane algebraic curves of degree eight that cannot be realized as T-curves, i.e., via combinatorial patchworking. In fact, this holds for several re…
Lower Bounds for Frank-Wolfe on Strongly Convex Sets
Jannis Halbey, Daniel Deza, Max Zimmer +3
We present a constructive lower bound of for Frank-Wolfe (FW) when both the objective and the constraint set are smooth and strongly convex, showing that…