---
title: "Xiangyu Wen — author profile and papers · Summarization"
description: "Xiangyu Wen, Chinese University of Hong Kong: 2 papers on Elamur Research (2026), h-index 1 — affiliations, topics, co-authors and who…"
canonical: "https://research.elamur.ai/free/en/authors/xiangyu-wen/"
---
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# Xiangyu Wen

Xiangyu Wen has 2 papers in our library, in 2026, most of them on [Summarization](https://md.research.elamur.ai/free/en/topics/summarization/), [Dialogue systems](https://md.research.elamur.ai/free/en/topics/dialogue-systems/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/); often with [Da Chen](https://md.research.elamur.ai/free/en/authors/da-chen/), [Zhijian Xu](https://md.research.elamur.ai/free/en/authors/zhijian-xu/).

2 papers in our library · 2026

[OpenAlex](https://openalex.org/A5100598437) · [**h-index 1**](https://openalex.org/authors/A5100598437) · [9 works](https://openalex.org/works?filter=author.id:A5100598437) · [7 citations](https://openalex.org/works?filter=author.id:A5100598437&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/xiangyu-wen/#papers) · [⭐ Paper Stars ranking: #13183](https://md.research.elamur.ai/free/en/paper-stars/page/132/#star-13183)

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Xiangyu+Wen) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Xiangyu+Wen) · [dblp](https://dblp.org/search?q=Xiangyu+Wen) · [ACL Anthology](https://aclanthology.org/search/?q=Xiangyu+Wen)

## Affiliations

[🎓**Chinese University of Hong Kong** Hong Kong · China 2024–2026 · 5 papers*current*](https://md.research.elamur.ai/free/en/universities/chinese-university-of-hong-kong/) · [🎓**Lanzhou University of Technology** Lanzhou · China 2023–2026 · 5 papers*current*](https://ror.org/03panb555)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

## Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 4 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/)

🧭 Topics 4 Research subjects and languages the work is about.[Dialogue systems · 1 work](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Summarization · 1 work](https://md.research.elamur.ai/free/en/topics/summarization/)

## Works by year

### 2020s

[**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/xiangyu-wen/year/2026/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Solve-Detect-Verify: Inference-Time Scaling with Flexible Generative Verifier](https://md.research.elamur.ai/free/en/papers/zhong-2026-solve-detect-verify-inference-time/)** *(2026 · 1 citation)* Step-by-step reasoning in LLMs creates a cost problem. Solvers keep generating text after they already have an answer, and checking their work is expensive. Process-based verifiers such as GenPRM re-read the context at every step. Cheap "NoThinking"-style checks are fast but flag many false positives.
2. **[Beyond Overlap Metrics: Rewarding Reasoning and Preferences for Faithful Multi-Role Dialogue Summarization](https://md.research.elamur.ai/free/en/papers/mei-2026-beyond-overlap-metrics-rewarding-reasoning/)** *(2026)* The paper addresses the problem that summarizers of multi-speaker conversations are usually tuned toward overlap metrics such as ROUGE and BERTScore.

## Co-authors here

2 co-authors with a page, the most papers together first.

- [Da Chen](https://md.research.elamur.ai/free/en/authors/da-chen/)
- [Zhijian Xu](https://md.research.elamur.ai/free/en/authors/zhijian-xu/)

## 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)](https://md.research.elamur.ai/free/en/venues/acl/): [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/)
- [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/): [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/)

Updated 1 November 2026
