Tootfinder

From Shadow to Light: Toward Safe and Efficient Policy Learning Across MPC, DeePC, RL, and LLM Agents
Amin Vahidi-Moghaddam, Sayed Pedram Haeri Boroujeni, Iman Jebellat, Ehsan Jebellat, Niloufar Mehrabi, Zhaojian Li
https://arxiv.org/abs/2510.04076

From Shadow to Light: Toward Safe and Efficient Policy Learning Across MPC, DeePC, RL, and LLM Agents
One of the main challenges in modern control applications, particularly in robot and vehicle motion control, is achieving accurate, fast, and safe movement. To address this, optimal control policies have been developed to enforce safety while ensuring high performance. Since basic first-principles models of real systems are often available, model-based controllers are widely used. Model predictive control (MPC) is a leading approach that optimizes performance while explicitly handling safety co…

NoLBERT: A No Lookahead(back) Foundational Language Model for Empirical Research
Ali Kakhbod, Peiyao Li
https://arxiv.org/abs/2509.01110 https://arxiv.org/…

NoLBERT: A No Lookahead(back) Foundational Language Model for Empirical Research
We present NoLBERT, a lightweight, timestamped foundational language model for empirical research in social sciences, particularly in economics and finance. By pre-training exclusively on 1976-1995 text, NoLBERT avoids both lookback and lookahead biases that can undermine econometric inference. It exceeds domain-specific baselines on NLP benchmarks while maintaining temporal consistency. Applied to patent texts, NoLBERT enables the construction of firm-level innovation networks and shows that g…

Teil der deutschen Produktionsketten (II) https://www.german-foreign-policy.com/news/detail/10082

Layered Normalized Min-Sum Decoding with Bit Flipping for FDPC Codes
Niloufar Hosseinzadeh, Mohsen Moradi, Hessam Mahdavifar
https://arxiv.org/abs/2510.01019 https://

Layered Normalized Min-Sum Decoding with Bit Flipping for FDPC Codes
Fair-density parity-check (FDPC) codes have been recently introduced demonstrating improved performance compared to low-density parity-check (LDPC) codes standardized in 5G systems particularly in high-rate regimes. In this paper, we introduce a layered normalized min-sum (LNMS) message-passing decoding algorithm for the FDPC codes. We also introduce a syndrome-guided bit flipping (SGBF) method to enhance the error-correction performance of our proposed decoder. The LNMS decoder leverages confl…

Exploring post-neoliberal futures for managing commercial heating and cooling through speculative praxis
Oliver Bates, Christian Remy, Kieran Cutting, Adam Tyler, Adrian Friday
https://arxiv.org/abs/2507.19072

Exploring post-neoliberal futures for managing commercial heating and cooling through speculative praxis
What could designing for carbon reduction of heating and cooling in commercial settings look like in the near future? How can we challenge dominant mindsets and paradigms of efficiency and behaviour change? How can we help build worlds through our practice that can become future realities? This paper introduces the fictional consultancy ANCSTRL.LAB to explore opportunities for making space in research projects that can encourage more systems-oriented interventions. We present a design fiction t…

NLAFormer: Transformers Learn Numerical Linear Algebra Operations
Zhantao Ma, Yihang Gao, Michael K. Ng
https://arxiv.org/abs/2508.19557 https://arxiv.org/…

NLAFormer: Transformers Learn Numerical Linear Algebra Operations
Transformers are effective and efficient at modeling complex relationships and learning patterns from structured data in many applications. The main aim of this paper is to propose and design NLAFormer, which is a transformer-based architecture for learning numerical linear algebra operations: pointwise computation, shifting, transposition, inner product, matrix multiplication, and matrix-vector multiplication. Using a linear algebra argument, we demonstrate that transformers can express such o…

Lasso Penalization for High-Dimensional Beta Regression Models: Computation, Analysis, and Inference
Niloofar Ramezani, Martin Slawski
https://arxiv.org/abs/2507.20079 https://

Lasso Penalization for High-Dimensional Beta Regression Models: Computation, Analysis, and Inference
Beta regression is commonly employed when the outcome variable is a proportion. Since its conception, the approach has been widely used in applications spanning various scientific fields. A series of extensions have been proposed over time, several of which address variable selection and penalized estimation, e.g., with an $\ell_1$-penalty (LASSO). However, a theoretical analysis of this popular approach in the context of Beta regression with high-dimensional predictors is lacking. In this pape…

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Generalized Quasispecies Model with Time Delays and Periodic Fluctuations in Replication
Nolbert Morales, Edward A. Turner
https://arxiv.org/abs/2508.12424 https://

Generalized Quasispecies Model with Time Delays and Periodic Fluctuations in Replication
In this research, we present a generalized quasispecies model in which population growth is governed by an arbitrary nonlinear function incorporating time delays. We begin by demonstrating that, under the constant population constraint, the dynamics of the system with time delays remain confined to the invariant manifold for both forward and backward time evolution. Furthermore, we establish that in this modified quasispecies model, defined on a single-peak fitness landscape, in the presence of…

Book Chapters: Women Athletes in Contemporary Art. Representations of the Gendered Paradox in Neoliberal Literature and Film https://call-for-papers.sas.upenn.edu/cfp/2025/09/13/book-chapters-women-athletes-in-co…