🧑‍🔬 Xin Wu

🏛️ Affiliations

🎓South China University of TechnologyGuangzhou · China2026 · 3 papersEmploymentcurrent🏢JingdongBeijing · China2026 · 1 papercurrent

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. PaCoRe: Learning to Scale Test-Time Compute with Parallel Coordinated Reasoning (2026 · 5 citations)
   Language models that reason step by step in a single chain hit a hard limit: once the context window is full, reasoning must stop.
2. BaichuanSEED: Sharing the Potential of ExtensivE Data Collection and Deduplication by Introducing a Competitive Large Language Model Baseline (2024 · 2 citations)
   Pre-training corpora largely determine what a large language model can do. Yet many developers, including some that release open weights, keep their data collection and mixing recipes private. Some models are also tuned toward particular benchmarks, which hides their real abilities.
3. SpecEdit: A Spectral Approach for Multi-Round Knowledge Editing (2026)
   Repeated batch editing of a large language model tends to wear down quality over time. Newly inserted facts are written less reliably, paraphrased queries generalize worse, and neighbouring knowledge gets disturbed. The authors study this in locate-then-edit methods such as MEMIT and AlphaEdit. In these methods, the…
4. Truth or Sophistry? LoFa: A Benchmark for LLM Robustness Against Logical Fallacies (2026)
   Most research on LLMs and logical fallacies tests whether models can name or classify a flawed argument. This paper asks a different question: can a model hold onto a correct answer when someone pushes fallacious reasoning at it? Earlier debate-style studies such as LOGICOM used contested opinion topics, so a model…

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. PaCoRe: Learning to Scale Test-Time Compute with Parallel Coordinated ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Jingcheng Hu, Yinmin Zhang, Shijie Shang, et al.2026 · 5 citations
2. BaichuanSEED: Sharing the Potential of ExtensivE Data Collection and Deduplication by Introducing a Competitive Large Language Model BaselinearXiv:2408.15079Guosheng Dong, Da Pan, Yiding Sun, et al.2024 · 2 citations
3. SpecEdit: A Spectral Approach for Multi-Round Knowledge EditingFindings of the Association for Computational LinguisticsJunxian Liu, Zikun Deng, Xin Wu, et al.2026
4. Truth or Sophistry? LoFa: A Benchmark for LLM Robustness Against Logical FallaciesAnnual Meeting of the Association for Computational Linguistics (ACL)Xudong Shen, li Yuan, Ye Chen, et al.2026
5. Unlocking Human-Like Visible Logic: How Logic Diagrams Boost Logic Reasoning in Large Language Models? ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetXin Wu et al.2026

🤝 Co-authors here

12 of 20 co-authors with a page, the most papers together first.

• Yi Cai ×2
• Chengyuan Yao
• Da Pan
• Fan Yang
• Fanqi Wan
• Guosheng Dong
• Haoze Sun
• Jianhua Xu
• Jingcheng Hu
• li Yuan
• Mingan Lin
• Shijie Shang

Venues

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

• Annual Meeting of the Association for Computational Linguistics (ACL) ×2: ACL 2026 ×2
• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
• Findings of the Association for Computational Linguistics: ACL 2026

🔗 Cited by

Papers of our library cite their works 7 times (of the 149,439 papers whose bibliographies we read); 3 citing papers with a page here →.

Updated 1 November 2026

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