302 citations · 459 across the 56 of their papers we have counts for
13 papers · 1 filter
Mitigating Social Bias in Large Language Models: A Multi-Objective Approach within a Multi-Agent Framework
Zhenjie Xu, Wenqing Chen, Yi Tang +6
Natural language processing (NLP) has seen remarkable advancements with the development of large language models (LLMs). Despite these advancements, LLMs often produce socially bia…
Euclid preparation: TBD. The impact of line-of-sight projections on the covariance between galaxy cluster multi-wavelength observable properties -- insights from hydrodynamic simulations
Euclid Collaboration, A. Ragagnin, A. Saro +240
Cluster cosmology can benefit from combining multi-wavelength studies, which can benefit from characterising the correlation coefficients between different mass-observable relation…
Resurfaced CsPbBr3 Nanocrystals Enable Free Radical Thermal Polymerization of Efficient Ultrafast Polyvinyl Styrene Nanocomposite Scintillators
Francesco Carulli, Andrea Erroi, Francesco Bruni +13
Lead halide perovskite nanocrystals (LHP-NCs) embedded in a plastic matrix are highly promising for a variety of photonic technologies and are quickly gaining attention as ultrafas…
A novel Kagome uud-ddu spin order in Heisenberg spin-1/2 Clinoatacamite Cu(OH)Cl, the parent compound of Herbertsmithite
X. G. Zheng, M. Hagihala, I. Yamauchi +4
The newly identified field-induced up-up-down order in BaCoSbO etc. renewed attention on exotic phases in spin-1/2 triangular-lattice antiferromagnets. Here, we report…
Euclid preparation. The Cosmic Dawn Survey (DAWN) of the Euclid Deep and Auxiliary Fields
Euclid Collaboration, C. J. R. McPartland, L. Zalesky +288
Euclid will provide deep NIR imaging to 26.5 AB magnitude over 59 deg in its deep and auxiliary fields. The Cosmic DAWN survey complements the deep Euclid data with…
Learning Atoms from Crystal Structure
Andrij Vasylenko, Dmytro Antypov, Sven Schewe +4
Computational modelling of materials using machine learning, ML, and historical data has become integral to materials research. The efficiency of computational modelling is strongl…