From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 12 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 5Arts and Humanities · 4 works Computer Science · 4 works Artificial Intelligence · 4 works Language and Linguistics · 4 works Computer Vision and Pattern Recognition · 1 work

🧭 Topics 3Language models & pretraining · 2 works Reasoning · 2 works Efficient models & compression · 1 work

Works by year

2020s

20262 papers 20252 papers

Papers

The most cited first (OpenAlex and our library).

Chain-of-Reasoning: Towards Unified Mathematical Reasoning in Large Language Models via a Multi-Paradigm Perspective (2025 · 23 citations)
Current LLM math solvers are usually tuned for a single reasoning style. Some use natural-language chains of thought, others use executable code, and others use formal proofs. As a result, a model strong at arithmetic word problems often fails at theorem proving, and the reverse. The authors propose…
Find Your Optimal Teacher: Personalized Data Synthesis via Router-Guided Multi-Teacher Distillation (2026 · 13 citations)
Small LLMs are usually distilled by fine-tuning them on outputs from the most powerful available teacher. Prior work shows this can backfire: very strong teachers may produce answers that are too complex or too far from what the student can absorb. Earlier remedies (Mix, CAR) still make every candidate teacher answer…
TL;DR: Too Long, Do Re-weighting for Efficient LLM Reasoning Compression (2025 · 8 citations)
Reasoning-focused LLMs that generate long Chain-of-Thought (CoT) often overthink, spending many tokens even on easy questions. Existing compression approaches usually need laborious data labeling, model interpolation (as in CoT-Valve), or costly RL with length penalties.
Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training (2026 · 1 citation)
Continual pre-training of an LLM on a narrow target field, such as math, often causes catastrophic forgetting of general skills.

Co-authors here

12 of 31 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.

Annual Meeting of the Association for Computational Linguistics (ACL) ×3: ACL 2026 ×2, ACL 2025

Cited by

Papers of our library cite their works 38 times (of the 149,439 papers whose bibliographies we read); 18 citing papers with a page here →.

Updated 1 November 2026

This page in Markdown → https://md.research.elamur.ai/free/en/authors/xiao-liang/

🧑‍🔬 Xiao Liang

🏛️ Affiliations

🧭 Fields, topics and concepts

📅 Works by year

2020s

📄 Papers

🤝 Co-authors here

Venues

🔗 Cited by

Xiao Liang

Affiliations

Fields, topics and concepts

Works by year

Papers

Co-authors here

Cited by