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Massimiliano Ciaramita

Massimiliano Ciaramita

D-Index & Metrics

Computer Science

D-Index
36
Citations
5633
World Ranking
11251
National Ranking
4646

Overview

Massimiliano Ciaramita is affiliated with Google in the United States and conducts research primarily in the field of Computer Science, with a focus on Artificial Intelligence. Their work extends into several related subfields, including Sociology and Political Science, Computer Vision and Pattern Recognition, Information Systems, and General Social Sciences.

The main research topics covered by Ciaramita include:

  • Topic Modeling
  • Domain Adaptation and Few-Shot Learning
  • Multimodal Machine Learning Applications
  • Climate Change Communication and Perception
  • Expert Finding and Q&A Systems
  • Neural Networks and Applications
  • Explainable Artificial Intelligence (XAI)

The scientist's recent publications illustrate engagement with both environmental and technical challenges. Notable papers are:

  • CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims, 2020, Zurich Open Repository and Archive (University of Zurich)
  • ClimaText: A Dataset for Climate Change Topic Detection, 2020, arXiv (Cornell University)
  • Assessing Large Language Models on Climate Information, 2023, arXiv (Cornell University)
  • Zero-Shot Retrieval with Search Agents and Hybrid Environments, 2022, arXiv (Cornell University)
  • Decoding a Neural Retriever's Latent Space for Query Suggestion, 2022, arXiv (Cornell University)

Ciaramita collaborates frequently with a number of researchers, including:

  • Michelle Chen Huebscher
  • Christian Buck
  • Markus Leippold
  • Jannis Bulian
  • Afra Amini

Their work has been published predominantly in the venue arXiv (Cornell University), which accounts for the majority of their publications. Other venues include the Zurich Open Repository and Archive (University of Zurich) and the Repository for Publications and Research Data (ETH Zurich).

Best Publications

  • The CoNLL-2009 Shared Task: Syntactic and Semantic Dependencies in Multiple Languages

    Jan Hajiċ;Massimiliano Ciaramita;Richard Johansson;Daisuke Kawahara

  • Modelling ontology evaluation and validation

    Aldo Gangemi;Carola Catenacci;Massimiliano Ciaramita;Jos Lehmann

  • Learning to Rank Answers on Large Online QA Collections

    Mihai Surdeanu;Massimiliano Ciaramita;Hugo Zaragoza

  • Broad-Coverage Sense Disambiguation and Information Extraction with a Supersense Sequence Tagger

    Massimiliano Ciaramita;Yasemin Altun

  • A framework for benchmarking entity-annotation systems

    Marco Cornolti;Paolo Ferragina;Massimiliano Ciaramita

  • Learning to rank answers to non-factoid questions from web collections

    Mihai Surdeanu;Massimiliano Ciaramita;Hugo Zaragoza

  • Unsupervised learning of semantic relations between concepts of a molecular biology ontology

    Massimiliano Ciaramita;Aldo Gangemi;Esther Ratsch;Jasmin Šaric

  • A theoretical framework for ontology evaluation and validation.

    Aldo Gangemi;Carola Catenacci;Massimiliano Ciaramita;Jos Lehmann

  • Supersense tagging of unknown nouns in WordNet

    Massimiliano Ciaramita;Mark Johnson

  • Ranking very many typed entities on wikipedia

    Hugo Zaragoza;Henning Rode;Peter Mika;Jordi Atserias

  • Topical clustering of search results

    Ugo Scaiella;Paolo Ferragina;Andrea Marino;Massimiliano Ciaramita

  • Online learning from click data for sponsored search

    Massimiliano Ciaramita;Vanessa Murdock;Vassilis Plachouras

  • Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing

    Zhendong Zhao;Lan Du;Benjamin Börschinger;John K. Pate

  • Ask the Right Questions: Active Question Reformulation with Reinforcement Learning

    Christian Buck;Jannis Bulian;Massimiliano Ciaramita;Wojciech Paweł Gajewski

  • On Identifiability in Transformers

    Gino Brunner;Yang Liu;Damian Pascual;Oliver Richter

  • Ontology evaluation and validation An integrated formal model for the quality diagnostic task

    Aldo Gangemi;Carola Catenacci;Massimiliano Ciaramita;Jos Lehmann

  • System and method for revising natural language parse trees

    Giuseppe Attardi;Massimiliano Ciaramita

  • A noisy-channel approach to contextual advertising

    Vanessa Murdock;Massimiliano Ciaramita;Vassilis Plachouras

  • Explaining away ambiguity: learning verb selectional preference with Bayesian networks

    Massimiliano Ciaramita;Mark Johnson

  • To swing or not to swing: learning when (not) to advertise

    Andrei Broder;Massimiliano Ciaramita;Marcus Fontoura;Evgeniy Gabrilovich

  • CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims

    Thomas Diggelmann;Jordan L. Boyd-Graber;Jannis Bulian;Massimiliano Ciaramita

Frequent Co-Authors

Vanessa Murdock
Vanessa Murdock Amazon (United States)
Mark Johnson
Mark Johnson Macquarie University
Hugo Zaragoza
Hugo Zaragoza Amazon (United States)
Aldo Gangemi
Aldo Gangemi University of Bologna
Mihai Surdeanu
Mihai Surdeanu University of Arizona
Evgeniy Gabrilovich
Evgeniy Gabrilovich Google (United States)
Paolo Ferragina
Paolo Ferragina University of Pisa
Donald Metzler
Donald Metzler Google (United States)
Andrei Z. Broder
Andrei Z. Broder Google (United States)

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