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Title: Semantic generalizations in humans and machines

Speaker: Prof. Najoung Kim @ Boston University

Time : 15:00 ~ 16:00, Dec 16th, 2024

Location: Hybrid

• In-person: 400102
• Online: https://us02web.zoom.us/j/84284257609?pwd=H16rSx8A3bPqDNNm0sBcLHDtwM9Sk9.1 
  • Meeting ID: 842 8425 7609
  • Passcode: 566273

Language: English speech & English slides

Abstract: 

Do machines "understand"? Empirically addressing this question requires an operationalization of what it means to understand. In this talk, I will discuss three tests for machines grounded in formal semantic theories that characterize various aspects of human linguistic understanding, examining the capacities to assign adequate meaning representations to linguistic expressions, to track entities and their states in discourse, and to draw adequate inferences from complex expressions. Critically, these capacities must _generalize_ to unseen expressions. I will discuss the findings from these studies contextualized with respect to human capacities.

Bio:

Najoung Kim is an Assistant Professor at the Department of Linguistics and an affiliate faculty in the Department of Computer Science at Boston University. She is also currently a visiting faculty researcher at Google DeepMind. Before joining BU, she was a Faculty Fellow at the Center for Data Science at New York University and received her PhD in Cognitive Science at Johns Hopkins University. She is interested in studying meaning in both human and machine learners, especially ways in which they generalize to novel inputs and ways in which they treat implicit meaning. Her research has been supported by NSF and Google, and has received awards at venues such as ACL, GenBench, & *SEM.

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