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Zixuan Zhang

Zixuan Zhang has 2 papers in our library, in 2026, most of them on Language models & pretraining; often with Meng Jiang, Qingyu Yin, Changlong Yu.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 7 · 31 works · 227 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 67 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #10468

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

🏢AmazonSeattle · United States2024–2026 · 2 paperscurrent🎓Beijing Information Science & Technology UniversityBeijing · China2024–2026 · 2 paperscurrent🎓Tianjin University of Science and TechnologyTianjin · China2026 · 1 papercurrent🎓University of Illinois Urbana-ChampaignUrbana · United States2021–2024 · 10 papers🎓Shanghai Jiao Tong UniversityShanghai · China2019–2021 · 3 papers🎓Zhengzhou University of Light IndustryZhengzhou · China2022 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 6 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.

📚 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 worksComputational Theory and Mathematics · 1 work

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Learning to Optimize Multi-Objective Alignment Through Dynamic Reward Weighting (2026 · 4 citations)
    The paper addresses a weakness in multi-objective online RL for aligning LLMs. Combining rewards with fixed linear weights cannot reach solutions on non-convex parts of the Pareto front. It also keeps spending gradient effort on objectives that have already saturated. The authors propose dynamic reward weighting…
  2. Instant Personalized Large Language Model Adaptation via Hypernetwork (2026 · 2 citations)
    Tailoring LLMs to individual users with parameter-efficient fine-tuning works well. However, the "One-PEFT-Per-User" (OPPU) approach trains a separate adapter for every person, which is too costly for millions of users or for preferences that change over time. The authors propose Profile-to-PEFT (P2P), which replaces…

All works

5 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Abstract Meaning Representation Guided Graph Encoding and Decoding for Joint Information Extraction ↗Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yetZixuan Zhang, Heng Ji2021 · 111 citations
  2. RESIN-11: Schema-guided Event Prediction for 11 Newsworthy Scenarios ↗Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: System Demonstrations · no summary yetXinya Du et al.2022 · 38 citations
  3. Learning to Optimize Multi-Objective Alignment Through Dynamic Reward WeightingTransactions of the Association for Computational Linguistics (TACL)Yining Lu, Zilong Wang, Shiyang Li, et al.2026 · 4 citations
  4. RESIN-EDITOR: A Schema-guided Hierarchical Event Graph Visualizer and Editor ↗Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations · no summary yetKhanh Duy Nguyen et al.2023 · 4 citations
  5. Instant Personalized Large Language Model Adaptation via HypernetworkAnnual Meeting of the Association for Computational Linguistics (ACL)Zhaoxuan Tan, Zixuan Zhang, Haoyang Wen, et al.2026 · 2 citations

 Co-authors here

12 of 15 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 67 times (of the 149,439 papers whose bibliographies we read); 4 citing papers with a page here →.

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