no code implementations • 15 Nov 2023 • Sheshera Mysore, Zhuoran Lu, Mengting Wan, Longqi Yang, 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 • 3 Nov 2023 • Marios Papachristou, Longqi Yang, Chin-Chia Hsu
In various work contexts, such as meeting scheduling, collaborating, and project planning, collective decision-making is essential but often challenging due to diverse individual preferences, varying work focuses, and power dynamics among members.
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.
no code implementations • 4 Feb 2022 • Mengyue Hang, Tobias Schnabel, Longqi Yang, Jennifer Neville
Most work in graph-based recommender systems considers a {\em static} setting where all information about test nodes (i. e., users and items) is available upfront at training time.
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.
no code implementations • NeurIPS 2021 • Longqi Yang, Liangliang Zhang, Wenjing Yang
This paper studies a long-standing problem of learning the representations of a whole graph without human supervision.
no code implementations • 7 Aug 2021 • Jyun-Yu Jiang, Chia-Jung Lee, Longqi Yang, Bahareh Sarrafzadeh, Brent Hecht, Jaime Teevan
Then we incorporate the resulting representations for enhancing the experiences of common activities people perform on the web.
no code implementations • 17 Jun 2021 • Rosie Jones, Hamed Zamani, Markus Schedl, Ching-Wei Chen, Sravana Reddy, Ann Clifton, Jussi Karlgren, Helia Hashemi, Aasish Pappu, Zahra Nazari, Longqi Yang, Oguz Semerci, Hugues Bouchard, Ben Carterette
Podcasts are spoken documents across a wide-range of genres and styles, with growing listenership across the world, and a rapidly lowering barrier to entry for both listeners and creators.
no code implementations • 3 Mar 2021 • Jenna Butler, Mary Czerwinski, Shamsi Iqbal, Sonia Jaffe, Kate Nowak, Emily Peloquin, Longqi Yang
We now turn to understanding the impact that COVID-19 had on the personal productivity and well-being of information workers as their work practices were impacted by remote work.
no code implementations • 18 Apr 2019 • Longqi Yang, Chen Fang, Hailin Jin, Walter Chang, Deborah Estrin
Complex design tasks often require performing diverse actions in a specific order.
2 code implementations • WWW 2017 • Cheng-Kang Hsieh, Longqi Yang, Yin Cui, Tsung-Yi Lin, Serge Belongie, Deborah Estrin
Metric learning algorithms produce distance metrics that capture the important relationships among data.
Ranked #1 on Recommendation Systems on MovieLens 20M (Recall@100 metric)
2 code implementations • 25 May 2016 • Longqi Yang, Cheng-Kang Hsieh, Hongjian Yang, Nicola Dell, Serge Belongie, Curtis Cole, Deborah Estrin
We propose Yum-me, a personalized nutrient-based meal recommender system designed to meet individuals' nutritional expectations, dietary restrictions, and fine-grained food preferences.
no code implementations • 21 Dec 2015 • Longqi Yang, Cheng-Kang Hsieh, Deborah Estrin
User preference profiling is an important task in modern online social networks (OSN).
no code implementations • 17 Mar 2014 • Longqi Yang, Yibing Wang, Zhisong Pan, Guyu Hu
In this paper, we apply the multi-task feature selection in network anomaly detection area which provides a powerful method to gather information from multiple traffic and detect anomalies on it simultaneously.