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Jun Xiao

Jun Xiao has 4 papers in our library, in 2026, most of them on Reasoning, Language models & pretraining; often with Weiming Lu, Yongliang Shen, Wenqi Zhang.

4 papers in our library · 2026

OpenAlex · h-index 1 · 12 works · 1 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 1 time in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #11049

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

 Papers

The most cited first (OpenAlex and our library).

  1. 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.
  2. 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.
  3. Experience-driven Multi-turn Reinforcement Learning for GUI Agents (2026)
    Training vision-based GUI agents for long, multi-step tasks involves a trade-off. Single-turn RL methods such as GRPO learn from expert histories, but at deployment the agent must rely on its own past actions, so training and real use differ. Online multi-turn RL closes this gap, but it brings sparse rewards, high…
  4. 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

5 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

  1. PILOT: Planning via Internalized Latent Optimization Trajectories for Large Language Models ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetHaoyu Zheng et al.2026

 Co-authors here

12 of 20 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 1 time (of the 149,439 papers whose bibliographies we read); 1 citing paper with a page here →.

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