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Carlos Toxtli

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Review Aug 2026

Prompt-Level Supervisory Alignment for Anticipatory Manuscript Revision

Researchers increasingly use large language models (LLMs) to revise manuscripts in response to peer reviews, yet this adoption is largely unprincipled and risks the ironies of automation. Prompt-Level Supervisory Alignment (PLSA) applies Supervisory Control Theory as a structured prompting strategy for LLM-assisted man...

Wangfan Li, Sofia Abilene Campos Hernandez, Carlos Toxtli · 0 citations
Book Open access Sep 2026

Personality-Profiled Virtual Agents Are More Predictable: The Constraint-Entropy Tradeoff for Trustworthy Agent Design

Effective human-agent cooperation requires that users form mental models of an agent’s behavioral tendencies. Yet LLM-based virtual agents are inherently stochastic, undermining the behavioral consistency that mental model formation depends on. We introduce the Constraint-Entropy Tradeoff (CET) model, an information-th...

Carlos Toxtli, M. Delaflor · 0 citations
#artificial intelligence Preprint Sep 2026

Randomized SVD Approximations for Spectral Co-Clustering of Word-Document Matrices

Spectral co-clustering is a useful tool for discovering latent structure in word-document matrices, but its reliance on singular value decomposition (SVD) can make standard formulations expensive on high-dimensional data. This paper presents two randomized approximations for normalized spectral co-clustering of biparti...

Fatemeh Mazdarani, Carlos Toxtli · 0 citations
#small language model Book Open access Sep 2026

Qualification by Calibration: A Readable Benchmark for Admitting Language Models to Human-Computation Tasks

Evaluating a diverse panel of contemporary models under three administration protocols, it is shown that a naive harness, with a fixed token budget and an unaudited parser, manufactures failing workers out of competent ones, misreading a model that answers essentially every item correctly as badly inaccurate, answer-bi...

Carlos Toxtli, M. Delaflor · 0 citations
Preprint Jul 2026

TREAT: Evaluating Access to Formal Knowledge across Equivalent Mathematical Representations

TREAT is introduced, a benchmark for evaluating whether large language models can recover known theorem identities from equivalence-preserving formula-level transformations, and provides a controlled testbed for evaluating representation-robust access to formal knowledge.

Fatemeh Mazdarani, Carlos Toxtli · 0 citations
#artificial intelligence Preprint Aug 2026

Beyond the Answer Key: Robustness Evaluation of Large Language Models for Step-Level Mathematical Verification

Evaluating state-of-the-art open LLMs reveals a significant robustness gap, and shows that reliable process-level verification remains challenging, and evaluator robustness should be measured separately from solver accuracy, even in a simple algebraic domain with exact ground truth.

Fatemeh Mazdarani, Carlos Toxtli · 2 citations
Open access Jul 2026

A Coupled AquaCrop–Richards Model for Improved Crop Yield Prediction Through Physically Based Soil Water Dynamics

Crop modelling is essential for agricultural water management but often relies on simplified water balance routines that limit representation of soil moisture dynamics. To address this limitation, we developed a coupled model that integrates the 1‐D Richards equation, solved using a finite difference method into th...

Krishna Panthi, Vidya S. Samadi, Carlos Toxtli · 1 citation

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