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Puyang Xu

Puyang Xu has 2 papers in our library, in 2018–2025, most of them on Dialogue systems; often with Bing Yin, Changlong Yu, Chao Zhang.

2 papers in our library · 2018–2025

OpenAlex · h-index 12 · 31 works · 870 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 83 times in our library · ⭐ Paper Stars ranking: #5485

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Duke UniversityDurham · United States2025 · 2 paperscurrent🎓University of VirginiaCharlottesville · United States2025 · 2 paperscurrent🎓Johns Hopkins UniversityBaltimore · United States2009–2011 · 4 papers🏢AmazonSeattle · United States2022–2023 · 2 papers🏢MicrosoftRedmond · United States2013–2014 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 work

🧭 Topics 1Research subjects and languages the work is about.Dialogue systems · 1 work

 Works by year

2020s

20251 paper

2010s

20181 paper

 Papers

The most cited first (OpenAlex and our library).

  1. An End-to-end Approach for Handling Unknown Slot Values in Dialogue State Tracking (2018 · 187 citations)
    Most dialogue state trackers assume a fixed ontology that lists every value a slot can take. In industrial settings this list is often unavailable, very large, or constantly changing. End-to-end trackers that work without an SLU module therefore cannot output values they have never been told about. Xu and Hu address…
  2. WebAgent-R1: Training Web Agents via End-to-End Multi-Turn Reinforcement Learning (2025 · 36 citations)
    Reinforcement learning has improved LLMs mostly on single-turn problems like math. Web agents are harder to train this way: they must make long sequences of decisions on changing pages, and earlier RL approaches for this setting depended on offline or off-policy pipelines with extra components. WebAgent-R1 is a…

 Co-authors here

10 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 83 times (of the 149,439 papers whose bibliographies we read); 19 citing papers with a page here →.

Updated

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