no code implementations • 30 Sep 2024 • Wenyue Hua, Mengting Wan, Shashank Vadrevu, Ryan Nadel, Yongfeng Zhang, Chi Wang
Agents, as user-centric tools, are increasingly deployed for human task delegation, assisting with a broad spectrum of requests by generating thoughts, engaging with user proxies, and producing action plans.
no code implementations • 28 Aug 2024 • Taiwei Shi, Zhuoer Wang, Longqi Yang, Ying-Chun Lin, Zexue He, Mengting Wan, Pei Zhou, Sujay Jauhar, Xiaofeng Xu, Xia Song, Jennifer Neville
As large language models (LLMs) continue to advance, aligning these models with human preferences has emerged as a critical challenge.
no code implementations • 19 Mar 2024 • Ying-Chun Lin, Jennifer Neville, Jack W. Stokes, Longqi Yang, Tara Safavi, Mengting Wan, Scott Counts, Siddharth Suri, Reid Andersen, Xiaofeng Xu, Deepak Gupta, Sujay Kumar Jauhar, Xia Song, Georg Buscher, Saurabh Tiwary, Brent Hecht, Jaime Teevan
Accurate and interpretable user satisfaction estimation (USE) is critical for understanding, evaluating, and continuously improving conversational systems.
no code implementations • 19 Mar 2024 • Siddharth Suri, Scott Counts, Leijie Wang, Chacha Chen, Mengting Wan, Tara Safavi, Jennifer Neville, Chirag Shah, Ryen W. White, Reid Andersen, Georg Buscher, Sathish Manivannan, Nagu Rangan, Longqi Yang
Until recently, search engines were the predominant method for people to access online information.
no code implementations • 18 Mar 2024 • Mengting Wan, Tara Safavi, Sujay Kumar Jauhar, Yujin Kim, Scott Counts, Jennifer Neville, Siddharth Suri, Chirag Shah, Ryen W White, Longqi Yang, Reid Andersen, Georg Buscher, Dhruv Joshi, Nagu Rangan
Transforming unstructured text into structured and meaningful forms, organized by useful category labels, is a fundamental step in text mining for downstream analysis and application.
no code implementations • 15 Nov 2023 • Sheshera Mysore, Zhuoran Lu, Mengting Wan, Longqi Yang, Bahareh Sarrafzadeh, Steve Menezes, Tina Baghaee, Emmanuel Barajas Gonzalez, Jennifer Neville, Tara Safavi
Powerful large language models have facilitated the development of writing assistants that promise to significantly improve the quality and efficiency of composition and communication.
no code implementations • 16 Sep 2023 • Sarkar Snigdha Sarathi Das, Chirag Shah, Mengting Wan, Jennifer Neville, Longqi Yang, Reid Andersen, Georg Buscher, Tara Safavi
The traditional Dialogue State Tracking (DST) problem aims to track user preferences and intents in user-agent conversations.
no code implementations • 14 Sep 2023 • Chirag Shah, Ryen W. White, Reid Andersen, Georg Buscher, Scott Counts, Sarkar Snigdha Sarathi Das, Ali Montazer, Sathish Manivannan, Jennifer Neville, Xiaochuan Ni, Nagu Rangan, Tara Safavi, Siddharth Suri, Mengting Wan, Leijie Wang, Longqi Yang
However, using LLMs to generate a user intent taxonomy and apply it for log analysis can be problematic for two main reasons: (1) such a taxonomy is not externally validated; and (2) there may be an undesirable feedback loop.
no code implementations • 11 Nov 2022 • Tobias Schnabel, Mengting Wan, Longqi Yang
With information systems becoming larger scale, recommendation systems are a topic of growing interest in machine learning research and industry.
no code implementations • 7 Jul 2022 • Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent Hecht, Jaime Teevan
Hypergraphs provide an effective abstraction for modeling multi-way group interactions among nodes, where each hyperedge can connect any number of nodes.
1 code implementation • 10 Jan 2022 • Jing Ma, Ruocheng Guo, Mengting Wan, Longqi Yang, Aidong Zhang, Jundong Li
In this framework, we generate counterfactuals corresponding to perturbations on each node's and their neighbors' sensitive attributes.
1 code implementation • 14 Jan 2020 • Zhiwei Liu, Mengting Wan, Stephen Guo, Kannan Achan, Philip S. Yu
By defining a basket entity to represent the basket intent, we can model this problem as a basket-item link prediction task in the User-Basket-Item~(UBI) graph.
1 code implementation • 4 Dec 2019 • Mengting Wan, Jianmo Ni, Rishabh Misra, Julian McAuley
However, these interactions can be biased by how the product is marketed, for example due to the selection of a particular human model in a product image.
2 code implementations • 27 Aug 2019 • An Yan, Shuo Cheng, Wang-Cheng Kang, Mengting Wan, Julian McAuley
Sequential patterns play an important role in building modern recommender systems.
no code implementations • ACL 2019 • Mengting Wan, Rishabh Misra, Ndapa Nakashole, Julian McAuley
This paper presents computational approaches for automatically detecting critical plot twists in reviews of media products.
no code implementations • 26 Nov 2018 • Mengting Wan, Xin Chen
We study the problem of providing recommended responses to customer service agents in live-chat dialogue systems.
2 code implementations • 29 Aug 2018 • Wang-Cheng Kang, Mengting Wan, Julian McAuley
Recommender Systems have proliferated as general-purpose approaches to model a wide variety of consumer interaction data.
no code implementations • 25 Oct 2016 • Mengting Wan, Julian McAuley
Product review websites provide an incredible lens into the wide variety of opinions and experiences of different people, and play a critical role in helping users discover products that match their personal needs and preferences.