2026-11-04T23:29:22Z https://edapress.org/oai

oai:edapress.org:eda-2026-0142 2026-06-24 cs

Attention Sparsity Patterns in Small Transformers Trained on Low-Resource Languages A. Mekonnen J. Park Computer Science transformers interpretability low-resource NLP We study how attention heads specialise when transformer models under 50M parameters are trained on corpora of fewer than 10 million tokens. Across five low-resource languages we find that induction heads emerge later and remain measurably sparser than in high-resource baselines, and that this sparsity predicts downstream transfer accuracy. We release our training code, checkpoints and evaluation harness. EDA 2026-06-24 Text info:eu-repo/semantics/article application/pdf https://doi.org/10.0000/eda.2026.0142 https://edapress.org/paper/eda-2026-0142 en CC BY 4.0

oai:edapress.org:eda-2026-0138 2026-06-02 earth

Mapping Urban Heat Islands with a Low-Cost Sensor Network Built by Secondary Students R. Osei M. Chen S. Villanueva Earth & Climate urban heat island open hardware citizen science Forty students deployed 96 open-hardware temperature sensors across a mid-sized city over one summer. We describe the calibration protocol, quantify drift against a reference station, and show the network resolves intra-city temperature differences of up to 4.2 degrees Celsius. Total hardware cost was under 900 USD. EDA 2026-06-02 Text info:eu-repo/semantics/article application/pdf https://doi.org/10.0000/eda.2026.0138 https://edapress.org/paper/eda-2026-0138 en CC BY 4.0

oai:edapress.org:eda-2026-0151 2026-07-09 quant

Shallow Variational Circuits for Constrained Portfolio Selection T. Fernandes Quantum variational algorithms QAOA finance We benchmark a depth-4 variational quantum circuit against classical solvers on constrained portfolio selection with up to 18 assets. On simulator and on trapped-ion hardware the quantum approach matches classical solutions for small instances but shows no advantage at this scale. We report full circuit definitions, seeds and device calibration so results can be reproduced. EDA 2026-07-09 Text info:eu-repo/semantics/article application/pdf https://doi.org/10.0000/eda.2026.0151 https://edapress.org/paper/eda-2026-0151 en CC BY 4.0

oai:edapress.org:eda-2026-0159 2026-08-14 soc

Cross-Age Peer Tutoring and Mathematics Anxiety: A Preregistered Field Study P. Okonkwo H. Lindqvist Social Science education preregistration maths anxiety In a preregistered study across four schools (n = 268), we test whether cross-age peer tutoring reduces self-reported mathematics anxiety. We find a small but robust effect concentrated in students starting in the lowest quartile, and no detectable effect on test scores within one term. EDA 2026-08-14 Text info:eu-repo/semantics/article application/pdf https://doi.org/10.0000/eda.2026.0159 https://edapress.org/paper/eda-2026-0159 en CC BY 4.0