The Open Virtual Assistant Lab seminar is a weekly event where students and researchers present their work in areas related to voice user interfaces, chatbots and virtual assistants. Topics include user interaction with natural language, chatbot-based applications, agent-to-agent distributed systems, question answering, natural language understanding and generation, and more.

The seminar is open to the Stanford community and members of the OVAL affiliate program. If you're interested to give a talk, please contact .

Mailing list: oval-seminar@lists.stanford.edu

Archive: Summer 2019

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9/27: Organizational Lunch

Time:

Location: Gates 463A (4th floor, B wing)

Organizational lunch. Come enjoy food and sign up to give a talk during the quarter.

10/4: Neural Program Synthesis from Natural Language Specification

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Location: Gates 463A (4th floor, B wing)

Abstract:
With the advancement of modern technologies, programming becomes ubiquitous not only among professional software developers, but also for general computer users. As a result, there has been an emerging interest in automatic program development. In this talk, I will mainly focus on my work on synthesizing programs from natural language descriptions, aiming at making programming systems more user-friendly. I will first discuss our work on translating natural language descriptions into If-Then programs, where If-Then programs have been adopted by several commercial websites including IFTTT, Zapier and Stringify. In the second part of my talk, I will discuss our recent work on neural-symbolic reasoning for reading comprehension. While reading comprehension has been widely considered as already solved by large-scale pre-trained language models such as BERT and XLNet, for questions that require more complex reasoning beyond text pattern matching, we find that language models themselves are insufficient. By equipping a pre-trained language model with a symbolic reasoning module that synthesizes and executes programs according to the natural language text, our Neural-symbolic Reader (NeRd) surpasses the state-of-the-art on DROP and MathQA, which are recent benchmarks that require challenging numerical reasoning, while also provides better interpretability.

Speaker: Xinyun Chen (UC Berkeley)
Xinyun Chen is a Ph.D. student at UC Berkeley, working with Prof. Dawn Song. She is also a student researcher at Google Brain, and was a research intern at Facebook AI Research. Her research lies at the intersection of deep learning, programming language, and security. Her recent work focuses on neural program synthesis and adversarial machine learning, towards tackling the grand challenges of increasing the accessibility of programming to general users, and enhancing the security and trustworthiness of machine learning models.

Food: Silei

10/11: HUBERT Untangles BERT to Improve Transfer across NLP Tasks

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Location: Gates 463A (4th floor, B wing)

Abstract:
We introduce HUBERT, which combines the structured-representational power of Tensor-Product Representations (TPRs) and BERT, a pre-trained bidirectional Transformer language model. We validate the effectiveness of our model on the GLUE benchmark and HANS dataset. We also show that there is shared structure between different NLP datasets which HUBERT, but not BERT, is able to learn and leverage. Extensive transfer-learning experiments are conducted to confirm this proposition.

Speaker: Mehrad Moradshahi
Mehrad Moradshahi is a Ph.D. student in the Stanford Computer Science department advised by Prof. Monica Lam. He also was a research intern at Microsoft Research where he focused on developing Transformer-based neuro-symbolic models for NLP tasks. He has been working mainly on the AI and natural language understanding side of the Almond project since 2018.

Food: Jian

10/18: TBA

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Location: Gates 463A (4th floor, B wing)

Abstract: TBA

Speaker: Jason Chou

Food: Euirim

10/25: TBA

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Location: Gates 463A (4th floor, B wing)

Abstract: TBA

Speaker: Peng Qi

11/1: TBA

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Location: Gates 463A (4th floor, B wing)

Abstract: TBA

Speaker: Silei Xu

11/8: TBA

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Location: Gates 463A (4th floor, B wing)

Abstract: TBA

Speaker: Chenglong Wang

11/15: TBA

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Location: Gates 463A (4th floor, B wing)

Abstract: TBA

Speaker: TBA

11/22: TBA

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Location: Gates 463A (4th floor, B wing)

Abstract: TBA

Speaker: TBA

11/29: Thanksgiving Recess

12/6: TBA

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Location: Gates 463A (4th floor, B wing)

Abstract: TBA

Speaker: TBA