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Wen Wang

Wen Wang has 8 papers in our library, in 2015–2026, most of them on Language models & pretraining, Named entity recognition, Machine translation; often with Qian Chen, Chenchen Jing, Chunhua Shen.

8 papers in our library · 2015–2026

OpenAlex · h-index 0 · 6 works · 0 citations OpenAlex, 2026-10-14

📄 8 works in our library · 🔗 Cited 87 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #5118

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

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

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

 Works by year

2020s

2010s

 Papers

The most cited first (OpenAlex and our library).

  1. Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition (2021 · 232 citations)
    The paper addresses nested named entity recognition, where entities can contain other entities. Span-based approaches handle nesting naturally, but they have four weaknesses: they enumerate many low-quality candidates, which is computationally costly; they cannot reach entities longer than the enumeration limit; they…
  2. OmniFlatten: An End-to-end GPT Model for Seamless Voice Conversation (2025 · 27 citations)
    Full-duplex voice assistants must listen and speak at the same time and cope with interruptions, overlapping speech and backchannels.
  3. ControlSpeech: Towards Simultaneous and Independent Zero-shot Speaker Cloning and Zero-shot Language Style Control (2025 · 10 citations)
    Text-to-speech systems have usually offered one of two abilities. Zero-shot models can copy an unseen speaker's voice but cannot change how that voice speaks. Style-controllable models follow textual style descriptions but cannot reproduce a chosen speaker's timbre. ControlSpeech combines both. It takes three inputs…
  4. Dual-Axis Generative Reward Model Toward Semantic and Turn-taking Robustness in Interactive Spoken Dialogue Models (2026 · 4 citations)
    Full-duplex spoken dialogue models (SDMs) must decide both what to say and when to say it. Reinforcement learning could improve this, but current automatic metrics make poor rewards. Timing-oracle proxies, event counts and metric suites each capture only part of interaction quality, and human ratings are expensive…
  5. Beyond Hard Masks: Progressive Token Evolution for Diffusion Language Models (2026 · 2 citations)
    Masked diffusion language models (MDLMs) generate text in parallel by gradually unmasking positions. They have two weaknesses. First, once a token is committed, it can never be revised. Second, the model predicts distributions for every position at each step but keeps only a few, so most of that work is thrown away.
  6. Efficient Self-Evaluation for Diffusion Language Models via Sequence Regeneration (2026 · 1 citation)
    Diffusion language models (dLLMs) such as LLaDA generate text by iteratively unmasking tokens in no fixed order.
  7. Exploiting Out-of-Domain Data Sources for Dialectal Arabic Statistical Machine Translation (2015 · 1 citation)
    Translating dialectal Arabic is hard because dialects are rarely written. Building parallel data means recording speech, transcribing it, and translating it, which is slow and costly. The authors target Iraqi Arabic (IA), where the in-domain resource is the Transtac corpus. They ask whether useful IA–English training…
  8. UniVocal: Unified Speech-Singing Code-Switching Synthesis (2026)
    The paper introduces Speech-Singing Code-Switching (SCS) Synthesis. In this task, a single generated utterance moves between talking and singing, and the text alone decides where the switches happen. Existing systems either produce only one mode or, like Bark, need explicit switching tags. The authors present…

All works

9 works of theirs in our library, the most cited first; 8 with a page here, the others link their original until we summarise them.

  1. Exploiting Out-of-Domain Data Sources for Dialectal Arabic Statistical Machine TranslationarXiv:1509.01938Katrin Kirchhoff, Bing Zhao, Wen Wang2015 · 1 citation
  2. GenesisFunc: Multi-Agent Data Generation for Accurate and Generalizable Function-Calling ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetHao-Xiang Xu et al.2026

 Co-authors here

12 of 25 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 87 times (of the 149,439 papers whose bibliographies we read); 11 citing papers with a page here →.

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