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Events for March

  • PhD Thesis Proposal - Emily Sheng

    Tue, Mar 03, 2020 @ 10:00 AM - 11:30 AM

    Thomas Lord Department of Computer Science

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    Title: Towards Fairness in Natural Language Processing

    Date/Time: Tuesday, March 3rd, 10-11:30am
    Location: SAL 213

    Candidate: Emily Sheng

    Committee: Prof. Prem Natarajan (advisor), Prof. Nanyun Peng, Prof. Aram Galstyan, Prof. Shri Narayanan, Prof. Yan Liu

    Abstract: With the advent of more effective, large-scale natural language processing (NLP) techniques, issues of fairness and bias in NLP techniques have become increasingly important. Biased models have the potential to perpetuate and amplify societal biases, which has implications for ethics, model robustness, and model interpretability. First, we describe our work to define biases in a language generation setting. We subsequently describe how different definitions of bias can be used to analyze biases in existing NLP systems, e.g., language generation and named entity recognition. Finally, we propose techniques that allow us to move towards the mitigation and control of biases. This talk will examine the importance of defining tasks and metrics for biases in NLP, how our bias analyses can inform our approach to bias mitigation, and related directions in how we can move towards fairness in NLP.

    Location: Henry Salvatori Computer Science Center (SAL) - 213

    Audiences: Everyone Is Invited

    Contact: Lizsl De Leon

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  • PhD Defense - Johnathan Mell

    Mon, Mar 09, 2020 @ 11:00 AM - 01:00 PM

    Thomas Lord Department of Computer Science

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    PhD Candidate: Johnathan Mell
    Date: Monday, March 9th, 2020
    Time: 11:00 AM - 1:00 PM
    Location: SAL 213
    Committee: Dr. Jonathan Gratch (Chair), Dr. Nate Fast, Dr. Sven Koenig

    Title: A Framework for Research in Human-Agent Negotiation


    Abstract:

    Increasingly, automated agents are interacting with humans in highly social interactions. Many of these interactions can be characterized as negotiation tasks. There has been broad research in negotiation techniques between humans (in business literatures, e.g.), as well a great deal of work in creating optimal agents that negotiate with each other. However, the creation of effective socially-aware agents requires fundamental basic research on human-agent negotiation. Furthermore, this line of enquiry requires highly customizable, fully-interactive systems that are capable of enabling and implementing human-agent interaction. Previous attempts that rely on hypothetical situations or one-shot studies are insufficient in capturing truly social behavior.

    This dissertation showcases my invention and development of the Interactive Arbitration Guide Online (IAGO) platform, which enables rigorous human-agent research. IAGO has been designed from the ground up to embody core principles gleaned from the rich body of research on how people actually negotiate. I demonstrate several examples of how IAGO has already yielded fundamental contributions towards our understanding of human-agent negotiation. I also demonstrate how IAGO has contributed to a community of practice by allowing researchers across the world to easily develop and investigate novel algorithms. Finally, I discuss future plans to use this framework to explore how humans and machines can establish enduring and profitable relationships through repeated negotiations.

    Location: Henry Salvatori Computer Science Center (SAL) - 213

    Audiences: Everyone Is Invited

    Contact: Lizsl De Leon

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