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Xue Zhang

Xue Zhang has 5 papers in our library, in 2024–2026, most of them on Multilingual & cross-lingual NLP, Language models & pretraining, Reasoning; often with Yufeng Chen, Songming Zhang, Fandong Meng.

5 papers in our library · 2024–2026

OpenAlex · ORCID · h-index 15 · 136 works · 921 citations OpenAlex, 2026-10-14

📄 5 works in our library · 🔗 Cited 76 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #7056

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. 37 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. Dual-Space Knowledge Distillation for Large Language Models (2024 · 39 citations)
    Standard white-box knowledge distillation for LLMs trains a small student to match the teacher's token-level output distributions.
  2. Multilingual Knowledge Editing with Language-Agnostic Factual Neurons (2025 · 17 citations)
    The paper tackles multilingual knowledge editing (MKE), which means changing a fact in an LLM so the correction holds in several languages at once.
  3. Less, but Better: Efficient Multilingual Expansion for LLMs via Layer-wise Mixture-of-Experts (2025 · 13 citations)
    Adding new languages to an existing LLM risks erasing skills in the languages it already handles well. The earlier MoE-based approach, MoE-LPR, also inflates model size: Qwen1.5-1.8B grows 3.2× to support three extra languages. This paper introduces LayerMoE, which questions whether every layer needs the same number…
  4. Think Natively: Unlocking Multilingual Reasoning with Consistency-Enhanced Reinforcement Learning (2026 · 11 citations)
    Reasoning-oriented LLMs that think before answering often handle non-English prompts poorly. They tend to drift into English or a mix of languages during reasoning, and their accuracy drops compared with English. The authors introduce M-Thinker, a family of models (1.5B, 4B, 7B) trained with GRPO using two new reward…
  5. Language-Coupled Reinforcement Learning for Multilingual Retrieval-Augmented Generation (2026 · 5 citations)
    The paper addresses two problems in multilingual retrieval-augmented generation (MRAG). The first is knowledge bias: an LLM answers the same question differently depending on its language. The second is knowledge conflict: passages retrieved from collections in many languages contradict each other. The authors…

All works

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

  1. A Quality-based Syntactic Template Retriever for Syntactically-Controlled Paraphrase Generation ↗Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · no summary yetXue Zhang et al.2023

 Co-authors here

12 of 13 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 76 times (of the 149,439 papers whose bibliographies we read); 14 citing papers with a page here →.

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