Vocabulary Alignment for Collaborative Agents: a Study with Real-World Multilingual How-to Instructions

Chocrón, Paula; Pareti, Paolo

doi:10.24963/ijcai.2018/22

Cited by 8 publications

(4 citation statements)

References 12 publications

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“…Given our aim to investigate concreteness ratings in context, we extracted the occurrences of the words to be annotated from natural examples. Sentences were derived from the English-Italian parallel section of The Human Instruction Dataset [51], a corpus that collects and organizes articles in machine-readable format from the WikiHow website in 16 languages. The whole Human Instruction Dataset is freely available on Kaggle at https://www.kaggle.com/paolop/…”

Section: Methodsmentioning

confidence: 99%

CONcreTEXT norms: Concreteness ratings for Italian and English words in context

Montefinese,

Gregori,

Ravelli

et al. 2023

PLoS ONE

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Concreteness is a fundamental dimension of word semantic representation that has attracted more and more interest to become one of the most studied variables in the psycholinguistic and cognitive neuroscience literature in the last decade. Concreteness effects have been found at both the brain and the behavioral levels, but they may vary depending on the constraints of the context and task demands. In this study, we collected concreteness norms for English and Italian words presented in different context sentences to allow better control and manipulation of concreteness in future psycholinguistic research. First, we observed high split-half correlations and Cronbach’s alpha coefficients, suggesting that our ratings were highly reliable and can be used in Italian- and English-speaking populations. Second, our data indicate that the concreteness ratings are related to the lexical density and accessibility of the sentence in both English and Italian. We also found that the concreteness of words in isolation was highly correlated with that of words in context. Finally, we analyzed differences between nouns and verbs in concreteness ratings without significant effects. Our new concreteness norms of words in context are a valuable source of information for future research in both the English and Italian language. The complete database is available on the Open Science Framework (doi: 10.17605/OSF.IO/U3PC4).

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Section: Methodsmentioning

confidence: 99%

CONcreTEXT norms: Concreteness ratings for Italian and English words in context

Montefinese,

Gregori,

Ravelli

et al. 2023

PLoS ONE

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show abstract

“…For example, if knowledge sources' provenance is dissimilar, simply aligning terminologies and concepts is not enough [58]. At this point, it is crucial to study models that allow handling contradictions, assumptions, explainable outcomes, and interpretations as part of the knowledge alignment task [59,60]. C4) Information uncertainty.…”

Section: Open Challengesmentioning

confidence: 99%

Towards Explainable Visionary Agents: License to Dare and Imagine

Ciatto

Najjar

Calbimonte

et al. 2021

Explainable and Transparent AI and Multi-Agent Systems

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Since their appearance, computer programs have embodied discipline and structured approaches and methodologies. Yet, to this day, equipping machines with imaginative and creative capabilities remains one of the most challenging and fascinating goals we pursue. Intelligent software agents can behave intelligently in well-defined scenarios, relying on Machine Learning (ML), symbolic reasoning, and the ability of their developers for tailoring smart behaviors to specific application domains. However, to forecast the evolution of all possible scenarios is unfeasible. Thus, intelligent agents should autonomously/creatively adapt to the world's mutability. This paper investigates the meaning of imagination in the context of cognitive agents. In particular, it addresses techniques and approaches to let agents autonomously imagine/simulate their course of action and generate explanations supporting it, and formalizes thematic challenges. Accordingly, we investigate research areas including: (i) reasoning and automatic theorem proving to synthesize novel knowledge via inference; (ii) automatic planning and simulation, used to speculate over alternative courses of action; (iii) machine learning and data mining, exploited to induce new knowledge from experience; and (iv) biochemical coordination, which keeps imagination dynamic by continuously reorganizing it.

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“…The dataset used for this task has been taken from the English-Italian parallel section of The Human Instruction Dataset (Chocron and Pareti, 2018), derived from WikiHow instructions. 1 All such documents had been anonymized beforehand, so that downloaded data present no privacy nor data sensitivity issues.…”

Section: Task Definitionmentioning

confidence: 99%

SSNCSE-NLP @ EVALITA2020: Textual and Contextual Stance Detection from Tweets Using Machine Learning Approach

Bharathi¹,

Bhuvana²,

Balaji³

2020

EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020

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Welcome to EVALITA 2020! EVALITA is the evaluation campaign of Natural Language Processing and Speech Tools for Italian. EVALITA is an initiative of the Italian Association for Computational Linguistics (AILC, http://www.ai-lc.it) and it is endorsed by the Italian Association for Artificial Intelligence (AIxIA, http://www.aixia.it) and the Italian Association for Speech Sciences (AISV, http://www.aisv.it).This volume includes the reports of both task organisers and participants to all of the EVALITA 2020 challenges. In the 2020 edition, we coordinated the organization of 14 different tasks belonging to five research areas, being: (i) Affect, Hate, and Stance, (ii) Creativity and Style, (iii) New Challenges in Long-standing Tasks, (iv) Semantics and Multimodality, Time and Diachrony.The volume is opened by an overview to the EVALITA 2020 campaign, in which we describe the tasks, provide statistics on the participants and task organizers as well as our supporting sponsors. The abstract of the keynote speech made by Preslav Nakov titled "Flattening the Curve of the COVID-19 Infodemic: These Evaluation Campaigns Can Help!" is also included in this collection.Due to the 2020 COVID-19 pandemic, the traditional workshop was held online, where several members of the Italian NLP Community presented the results of their research. Despite the circumstances, the workshop represented an occasion for all participants from both academic institutions and private companies to disseminate their work and results and to share ideas through online sessions dedicated to each task and a general discussion during the plenary event.We carried on with the tradition of the "Best system across tasks" award. As in 2018, it represented an incentive for students, IT developers and researchers to push the boundaries of the state of the art by facing tasks in new ways, even if not winning.

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Vocabulary Alignment for Collaborative Agents: a Study with Real-World Multilingual How-to Instructions

Cited by 8 publications

References 12 publications

CONcreTEXT norms: Concreteness ratings for Italian and English words in context

CONcreTEXT norms: Concreteness ratings for Italian and English words in context

Towards Explainable Visionary Agents: License to Dare and Imagine

SSNCSE-NLP @ EVALITA2020: Textual and Contextual Stance Detection from Tweets Using Machine Learning Approach

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