Evaluation of Distributional Semantic Models of Ancient Greek:Preliminary Results and a Road Map for Future Work

We evaluate four count-based and predictive distributional semantic models of Ancient Greek against AGREE, a composite benchmark of human judgements, to assess their ability to retrieve semantic relatedness. On the basis of the observations deriving from the analysis of the results, we design a procedure for a largerscale intrinsic evaluation of count-based and predictive language models, including syntactic embeddings. We also propose possible ways of exploiting the different layers of the whole AGREE benchmark (including both humanand machine-generated data) and different evaluation metrics

Evaluation of Distributional Semantic Models of Ancient Greek:Preliminary Results and a Road Map for Future Work

We evaluate four count-based and predictive distributional semantic models of Ancient Greek against AGREE, a composite benchmark of human judgements, to assess their ability to retrieve semantic relatedness. On the basis of the observations deriving from the analysis of the results, we design a procedure for a largerscale intrinsic evaluation of count-based and predictive language models, including syntactic embeddings. We also propose possible ways of exploiting the different layers of the whole AGREE benchmark (including both humanand machine-generated data) and different evaluation metrics

Evaluation of Distributional Semantic Models of Ancient Greek:Preliminary Results and a Road Map for Future Work

We evaluate four count-based and predictive distributional semantic models of Ancient Greek against AGREE, a composite benchmark of human judgements, to assess their ability to retrieve semantic relatedness. On the basis of the observations deriving from the analysis of the results, we design a procedure for a largerscale intrinsic evaluation of count-based and predictive language models, including syntactic embeddings. We also propose possible ways of exploiting the different layers of the whole AGREE benchmark (including both humanand machine-generated data) and different evaluation metrics

Evaluation of Distributional Semantic Models of Ancient Greek:Preliminary Results and a Road Map for Future Work

We evaluate four count-based and predictive distributional semantic models of Ancient Greek against AGREE, a composite benchmark of human judgements, to assess their ability to retrieve semantic relatedness. On the basis of the observations deriving from the analysis of the results, we design a procedure for a largerscale intrinsic evaluation of count-based and predictive language models, including syntactic embeddings. We also propose possible ways of exploiting the different layers of the whole AGREE benchmark (including both humanand machine-generated data) and different evaluation metrics

AGILe:The First Lemmatizer for Ancient Greek Inscriptions

To facilitate corpus searches by classicists as well as to reduce data sparsity when training models, we focus on the automatic lemmatization of ancient Greek inscriptions, which have not received as much attention in this sense as literary text data has. We show that existing lemmatizers for ancient Greek, trained on literary data, are not performant on epigraphic data, due to major language differences between the two types of texts. We thus train the first inscription-specific lemmatizer achieving above 80% accuracy, and make both the models and the lemmatized data available to the community. We also provide a detailed error analysis highlighting peculiarities of inscriptions which again highlights the importance of a lemmatizer dedicated to inscriptions

Chronic alcohol consumption alters extracellular space geometry and transmitter diffusion in the brain

[EN] Already moderate alcohol consumption has detrimental long-term effects on brain function. However, how alcohol produces its potent addictive effects despite being a weak reinforcer is a poorly understood conundrum that likely hampers the development of successful interventions to limit heavy drinking. In this translational study, we demonstrate widespread increased mean diffusivity in the brain gray matter of chronically drinking humans and rats. These alterations appear soon after drinking initiation in rats, persist into early abstinence in both species, and are associated with a robust decrease in extracellular space tortuosity explained by a microglial reaction. Mathematical modeling of the diffusivity changes unveils an increased spatial reach of extrasynaptically released transmitters like dopamine that may contribute to alcohol's progressively enhanced addictive potencyThis work was supported by the European Union's Horizon 2020 research and innovation program (668863-SyBil-AA) and the ERA-NET NEURON program (FKZ 01EW1112-TRANSALC and PIM2010ERN-00679), as well as the Spanish State Research Agency through the Severo Ochoa Program for Centres of Excellence in R&D (SEV-2017-0723), the Deutsche Forschungsgemeinschaft (center grant TRR265-B08), and the Czech Science Foundation (GACR; grant no. 16-10214S to L.V.). S.C. and D.M. further acknowledge financial support from the Ministerio de Economia y Competitividad (MINECO) and FEDER funds under grant nos. BFU2015-64380-C2-1-R, BFU2015-64380-C2-2-R, and PGC2018-101055-B-I00 and the Generalitat Valenciana through the Prometeo Program (PROMETEO/2019/015). S.C. also acknowledges support of the Ministerio de Sanidad, Servicios Sociales e Igualdad (#2017I065). E.S. acknowledges financial support from the Slovak Research and Development Agency (APVV-17-0642). S.D.S. is supported by a NARSAD Young Investigator Grant (grant no. 25104), by the European Research Council through a Marie Sklodowska-Curie Individual Fellowship (grant no. 749506), and by the Generalitat Valenciana grant SEJI/2019/038. R.C. is supported by the NIAAA grant AA017447. W.H.S acknowledges support from the Bundesministerium fur Bildung und Forschung (BMBF; FKZ: 031L0190A, 01ZX1909CA).De Santis, S.; Cosa-Liñán, A.; Garcia-Hernandez, R.; Dmytrenko, L.; Vargova, L.; Vorisek, I.; Stopponi, S.... (2020). Chronic alcohol consumption alters extracellular space geometry and transmitter diffusion in the brain. Science Advances. 6(26):1-12. https://doi.org/10.1126/sciadv.aba0154S11262

AGREE:a new benchmark for the evaluation of distributional semantic models of ancient Greek

The last years have seen the application of Natural Language Processing, in particular, language models, to the study of the Semantics of ancient Greek, but only a little work has been done to create gold data for the evaluation of such models. In this contribution we introduce AGREE, the first benchmark for intrinsic evaluation of semantic models of ancient Greek created from expert judgements. In the absence of native speakers, eliciting expert judgements to create a gold standard is a way to leverage a competence that is the closest to that of natives. Moreover, this method allows for collecting data in a uniform way and giving precise instructions to participants. Human judgements about word relatedness were collected via two questionnaires: in the first, experts provided related lemmas to some proposed seeds, while in the second, they assigned relatedness judgements to pairs of lemmas. AGREE was built from a selection of the collected data