12 research outputs found
Neural Simile Recognition with Cyclic Multitask Learning and Local Attention
Simile recognition is to detect simile sentences and to extract simile
components, i.e., tenors and vehicles. It involves two subtasks: {\it simile
sentence classification} and {\it simile component extraction}. Recent work has
shown that standard multitask learning is effective for Chinese simile
recognition, but it is still uncertain whether the mutual effects between the
subtasks have been well captured by simple parameter sharing. We propose a
novel cyclic multitask learning framework for neural simile recognition, which
stacks the subtasks and makes them into a loop by connecting the last to the
first. It iteratively performs each subtask, taking the outputs of the previous
subtask as additional inputs to the current one, so that the interdependence
between the subtasks can be better explored. Extensive experiments show that
our framework significantly outperforms the current state-of-the-art model and
our carefully designed baselines, and the gains are still remarkable using
BERT.Comment: AAAI 202
CM-Gen: a neural framework for Chinese metaphor generation with explicit context modelling
Nominal metaphors are frequently used in human language and have been shown to be effective in persuading, expressing emotion, and stimulating interest. This paper tackles the problem of Chinese Nominal Metaphor (NM) generation. We introduce a novel multitask framework, which jointly optimizes three tasks: NM identification, NM component identification, and NM generation. The metaphor identification module is able to perform a self-training procedure, which discovers novel metaphors from a large-scale unlabeled corpus for NM generation. The NM component identification module emphasizes components during training and conditions the generation on these NM components for more coherent results. To train the NM identification and component identification modules, we construct an annotated corpus consisting of 6.3k sentences that contain diverse metaphorical patterns. Automatic metrics show that our method can produce diverse metaphors with good readability, where 92% of them are novel metaphorical comparisons. Human evaluation shows our model significantly outperforms baselines on consistency and creativity
Proceedings of the Fifth Italian Conference on Computational Linguistics CLiC-it 2018 : 10-12 December 2018, Torino
On behalf of the Program Committee, a very warm welcome to the Fifth Italian Conference on Computational Linguistics (CLiC-‐it 2018). This edition of the conference is held in Torino. The conference is locally organised by the University of Torino and hosted into its prestigious main lecture hall “Cavallerizza Reale”. The CLiC-‐it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after five years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges
Proceedings of the Eighth Italian Conference on Computational Linguistics CliC-it 2021
The eighth edition of the Italian Conference on Computational Linguistics (CLiC-it 2021) was held at Università degli Studi di Milano-Bicocca from 26th to 28th January 2022. After the edition of 2020, which was held in fully virtual mode due to the health emergency related to Covid-19, CLiC-it 2021 represented the first moment for the Italian research community of Computational Linguistics to meet in person after more than one year of full/partial lockdown
Proceedings of the Fifth Italian Conference on Computational Linguistics CLiC-it 2018
On behalf of the Program Committee, a very warm welcome to the Fifth Italian Conference on Computational Linguistics (CLiC-‐it 2018). This edition of the conference is held in Torino. The conference is locally organised by the University of Torino and hosted into its prestigious main lecture hall “Cavallerizza Reale”. The CLiC-‐it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after five years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges
Basic Cell and Molecular Biology 5e: What We Know and How We Find Out
https://dc.uwm.edu/biosci_facbooks_bergtrom/1014/thumbnail.jp
Annotated Cell and Molecular Biology 5e: What We Know and How We Found Out
https://dc.uwm.edu/biosci_facbooks_bergtrom/1013/thumbnail.jp
Psychological Engagement in Choice and Judgment Under Risk and Uncertainty
Theories of choice and judgment assume that agents behave rationally, choose the higher expected value option, and evaluate the choice consistently (Expected Utility Theory, Von Neumann, & Morgenstern, 1947). However, researchers in decision-making showed that human behaviour is different in choice and judgement tasks (Slovic & Lichtenstein, 1968; 1971; 1973). In this research, we propose that psychological engagement and control deprivation predict behavioural inconsistencies and utilitarian performance with judgment and choice. Moreover, we explore the influences of engagement and control deprivation on agent’s behaviours, while manipulating content of utility (Kusev et al., 2011, Hertwig & Gigerenzer 1999, Tversky & Khaneman, 1996) and
decision reward (Kusev et al, 2013, Shafir et al., 2002)