Self-Adapter at SemEval-2021 Task 10: Entropy-based Pseudo-Labeler for Source-free Domain Adaptation

Source-free domain adaptation is an emerging line of work in deep learning research since it is closely related to the real-world environment. We study the domain adaption in the sequence labeling problem where the model trained on the source domain data is given. We propose two methods: Self-Adapter and Selective Classifier Training. Self-Adapter is a training method that uses sentence-level pseudo-labels filtered by the self-entropy threshold to provide supervision to the whole model. Selective Classifier Training uses token-level pseudo-labels and supervises only the classification layer of the model. The proposed methods are evaluated on data provided by SemEval-2021 task 10 and Self-Adapter achieves 2nd rank performance.

Fabula Entropy Indexing: Objective Measures of Story Coherence

Automated story generation remains a difficult area of research because it lacks strong objective measures. Generated stories may be linguistically sound, but in many cases suffer poor narrative coherence required for a compelling, logically-sound story. To address this, we present Fabula Entropy Indexing (FEI), an evaluation method to assess story coherence by measuring the degree to which human participants agree with each other when answering true/false questions about stories. We devise two theoretically grounded measures of reader question-answering entropy, the entropy of world coherence (EWC), and the entropy of transitional coherence (ETC), focusing on global and local coherence, respectively. We evaluate these metrics by testing them on human-written stories and comparing against the same stories that have been corrupted to introduce incoherencies. We show that in these controlled studies, our entropy indices provide a reliable objective measure of story coherence.

Kinetic And Thermal Study Of Resulted Poly Amide of Reaction Of 4,4′- M Ethylenebis (2- Methelcyclohexylamine) With Dimeric Fatty Acid C36 In The Precence and Absence Of Sulpheric Acid

Kinetic studies were carried out on the reaction between ′4,4-Methylenebis (2-methylcyclohexylamine) and dimeric fatty acid C36 in molten state by using a catalyst of sulpheric acid compared with the same kinetic of reaction without catalyst. The reaction was performed at 150, and 160 ˚C and followed by determining the acid value of the product.The polyamidation reaction was found to be of overall a second order until equilibrium state. Moreover, the catalyst increases speed of the reaction. Polyamidation reaction was automatic whereas the value of free energy was negative and the reaction was endothermic, and this is shown in change of positive enthalpy values.