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Xin Huang

Xin Huang has 3 papers in our library, in 2024–2026, most of them on Reasoning, Machine translation, Language models & pretraining; often with Shujian Huang, AiTi Aw, Bin Wang.

3 papers in our library · 2024–2026

OpenAlex · ORCID · h-index 19 · 102 works · 1,455 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 87 times in our library · ⭐ Paper Stars ranking: #6783

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. 24 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. SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural Reasoning (2024 · 85 citations)
    SeaEval is a benchmark for multilingual foundation models. It addresses gaps that monolingual and bilingual test suites leave open, namely cultural comprehension and whether a model's knowledge stays the same across languages. The benchmark covers four capability areas: classic NLP tasks, complex reasoning, cultural…
  2. R-PRM: Reasoning-Driven Process Reward Modeling (2025 · 18 citations)
    Process Reward Models (PRMs) score each step of an LLM's mathematical reasoning. Most existing PRMs output a score directly, which limits how well they learn and gives no explanation for a judgment. Step-level labeled data is also scarce. R-PRM addresses this by having the reward model write an analysis of each step…
  3. PEGRL: Improving Machine Translation by Post-Editing Guided Reinforcement Learning (2026)
    LLM translation trained with reinforcement learning (e.g., GRPO) suffers from two problems. Its Monte Carlo group baselines are noisy, and its huge output space rewards broad exploration but gives little signal for small local fixes. PEGRL addresses this by treating translation as a two-step workflow: a draft…

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

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