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Xiang Liu

Xiang Liu has 4 papers in our library, in 2024–2026, most of them on Language models & pretraining, Multilingual & cross-lingual NLP, Reasoning; often with Bo Li, Han Zhang, Jiajun Chen.

4 papers in our library · 2024–2026

OpenAlex · ORCID · Wikidata · h-index 5 · 10 works · 147 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 170 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #7467

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. 3 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. MAPO: Advancing Multilingual Reasoning through Multilingual-Alignment-as-Preference Optimization (2024 · 59 citations)
    Large language models tend to solve math word problems much better in English than in other languages, mainly because their training data is skewed toward English.
  2. CAFES: A Collaborative Multi-Agent Framework for Multi-Granular Multimodal Essay Scoring (2026 · 4 citations)
    Multimodal writing tasks ask students to argue from images such as charts. Scoring them automatically is hard. Classic AES systems depend on handcrafted features and cannot process images. Single-MLLM scorers tend to invent justifications and grade more harshly than human raters. CAFES addresses this by dividing…
  3. Mixture of Heterogeneous Grouped Experts for Language Modeling (2026)
    Standard Mixture-of-Experts (MoE) language models use experts of one fixed size, so every token receives the same compute regardless of how hard it is to predict.
  4. Probing the Plasticity and Correlation of LLM Value Systems: LLM Value Rankings are Not Stable (2026)
    Earlier work found that different LLMs rank their values in similar ways. This paper asks whether those rankings stay fixed when the model is pushed by its context, and whether some values tend to shift together. The authors build on the LITMUSVALUES setup. Models face two-action dilemmas, each action tied to one of…

All works

7 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. Active Prompting with Chain-of-Thought for Large Language Models ↗arXiv:2302.12246 · no summary yetShizhe Diao et al.2023 · 201 citations
  2. DiffAdapt: Difficulty-Adaptive Reasoning for Token-Efficient LLM Inference ↗arXiv (Cornell University) · no summary yetXiang Liu et al.2025 · 2 citations
  3. Are Dilemmas and Conflicts in LLM Alignment Solvable? A View from Priority Graph ↗arXiv (Cornell University) · no summary yetZhenheng Tang et al.2026 · 1 citation

 Co-authors here

12 of 16 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 170 times (of the 149,439 papers whose bibliographies we read); 41 citing papers with a page here →.

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