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Wenqi Zhang

Wenqi Zhang has 7 papers in our library, in 2024–2026, most of them on Reasoning, Language models & pretraining, Code & programming languages; often with Weiming Lu, Yongliang Shen, Guiyang Hou.

7 papers in our library · 2024–2026

OpenAlex · ORCID · Wikidata · h-index 15 · 85 works · 885 citations OpenAlex, 2026-10-14

📄 7 works in our library · 🔗 Cited 119 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #6181

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. 18 more institutions on single bylines are not listed.

 Fields, topics and concepts

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

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. Self-Contrast: Better Reflection Through Inconsistent Solving Perspectives (2024 · 75 citations)
    The paper asks why large language models rarely fix their own mistakes when they reflect without outside feedback.
  2. Agent-Pro: Learning to Evolve via Policy-Level Reflection and Optimization (2024 · 52 citations)
    Most LLM-based agents depend on hand-written prompts that fix task rules and behavior. They cannot improve through experience, so they struggle in dynamic multi-agent settings with hidden information. Agent-Pro tackles this by treating policy learning as gradient-free prompt optimization, with no parameter updates.
  3. STaR-SQL: Self-Taught Reasoner for Text-to-SQL (2025 · 17 citations)
    Text-to-SQL systems built on LLMs often depend on long, rigid prompt pipelines, such as GPT-4-based DIN-SQL.
  4. Embodied-Reasoner: Synergizing Visual Search, Reasoning, and Action for Embodied Interactive Tasks (2026 · 5 citations)
    Reasoning models do well at math and coding, but it is unclear whether they can handle embodied tasks. In these tasks an agent explores a room over many turns and must work with long sequences of alternating images and text. The authors present Embodied-Reasoner, a vision-language agent that combines visual search…
  5. CoVerRL: Breaking the Consensus Trap in Label-Free Reasoning via Generator-Verifier Co-Evolution (2026 · 1 citation)
    Label-free reinforcement learning for LLM reasoning usually rewards a model for matching its own majority-voted answer.
  6. UI-Copilot: Advancing Long-Horizon GUI Automation via Tool-Integrated Policy Optimization (2026 · 1 citation)
    Multimodal GUI agents perform well on short mobile tasks but break down on long, memory-heavy ones. Existing 7B models lose about 90.9% of their accuracy on MemGUI-Bench. The authors trace these failures to three causes: forgetting earlier observations, losing track of task progress, and making arithmetic mistakes.
  7. Pause or Fabricate? Training Language Models for Grounded Reasoning (2026)
    The paper examines a failure mode the authors call ungrounded reasoning. When a question lacks a needed fact, a language model often notices the gap early but then invents a value and reasons confidently to a wrong answer. The authors argue that the cause is weak awareness of when valid inference is possible, not…

All works

8 works of theirs in our library, the most cited first; 7 with a page here, the others link their original until we summarise them.

  1. PromptNER: Prompt Locating and Typing for Named Entity Recognition ↗Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetYongliang Shen et al.2023 · 83 citations

 Co-authors here

12 of 23 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 119 times (of the 149,439 papers whose bibliographies we read); 22 citing papers with a page here →.

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