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.
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
Affiliations
Fields, topics and concepts
📚 Shelves 8The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 4 worksComputer Science · 4 worksArtificial Intelligence · 4 worksLanguage and Linguistics · 4 worksComputer Vision and Pattern Recognition · 1 workInformation Systems · 1 workSafety Research · 1 workSocial Sciences · 1 work
🧭 Topics 6Research subjects and languages the work is about.Multilingual & cross-lingual NLP · 1 workReasoning · 1 workGrammatical error correction & learner language · 1 workVision & language · 1 workLanguage models & pretraining · 2 worksInterpretability · 1 work
Works by year
2020s
Papers
- 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. - 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… - 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. - 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
- Active Prompting with Chain-of-Thought for Large Language Models ↗arXiv:2302.12246 · no summary yetShizhe Diao et al.2023 · 201 citations
- MAPO: Advancing Multilingual Reasoning through Multilingual-Alignment-as-Preference OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Shuaijie She, Wei Zou, Shujian Huang, et al.2024 · 59 citations
- CAFES: A Collaborative Multi-Agent Framework for Multi-Granular Multimodal Essay ScoringWorkshop on Advances in Language and Vision Research (ALVR)Jiamin Su, Yibo Yan, Zhuoran Gao, et al.2026 · 4 citations
- DiffAdapt: Difficulty-Adaptive Reasoning for Token-Efficient LLM Inference ↗arXiv (Cornell University) · no summary yetXiang Liu et al.2025 · 2 citations
- 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
- Mixture of Heterogeneous Grouped Experts for Language ModelingAnnual Meeting of the Association for Computational Linguistics (ACL)Zhicheng Ma, Xiang Liu, Zhaoxiang Liu, et al.2026
- Probing the Plasticity and Correlation of LLM Value Systems: LLM Value Rankings are Not StableFindings of the Association for Computational LinguisticsZhenheng Tang, Qihua Pan, Jingya Shen, et al.2026
Co-authors here
- Bo Li
- Han Zhang
- Jiajun Chen
- Jiamin Su
- Kai Wang
- Ning Wang
- Qian Wang
- Shiguo Lian
- Shuaijie She
- Shujian Huang
- Shuming Shi
- Wenhao Zhu
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL) ×2: ACL 2026, ACL 2024
- Workshop on Advances in Language and Vision Research (ALVR): ALVR 2026
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
Cited by
Updated
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