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Shiquan Wang

Shiquan Wang has 3 papers in our library, in 2026, most of them on Language models & pretraining, Sentiment & emotion, Reasoning; often with Shuangyong Song, Xuelong Li, Fang Yu.

3 papers in our library · 2026

OpenAlex · h-index 0 · 4 works · 0 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 1 time in our library · ⭐ Paper Stars ranking: #12792

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

🏢China TelecomBeijing · China2026 · 4 paperscurrent

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 7The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 3 worksArts and Humanities · 3 worksComputer Science · 3 worksLanguage and Linguistics · 3 worksExperimental and Cognitive Psychology · 1 workPsychology · 1 workInformation Systems · 1 work

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 1 workSentiment & emotion · 1 workReasoning · 1 work

 Works by year

2020s

20263 papers

 Papers

The most cited first (OpenAlex and our library).

  1. TeleAI at SemEval-2026 Task 3: Large Language Models for Dimensional Aspect-Based Sentiment Analysis (2026 · 1 citation)
    This paper describes TeleAI's entry for Track A, Subtask 1 (DimASR) of SemEval-2026 Task 3. In this task, sentiment toward each aspect term is not a polarity label but a pair of continuous Valence–Arousal (VA) scores between 1 and 9, scored with RMSE_VA. The authors treat the problem as direct regression. The input…
  2. TeleAI at SemEval-2026 Task 13: Data-Centric Full-Parameter Fine-Tuning with Multi-Level Ensembling for Generated Code Detection (2026)
    The paper describes TeleAI's entry to SemEval-2026 Task 13, which focuses on telling human-written source code apart from LLM-generated code. The task has three subtasks:
  3. TeleAI at SemEval-2026 Task 6: A Confidence-Aware Multi-Stage Reasoning Framework with Chain-of-Thought (2026)
    The paper presents TeleAI's winning system for SemEval-2026 Task 6 (CLARITY). The task asks whether answers in English political interviews actually respond to a given sub-question. SubTask 1 uses three coarse clarity labels, and SubTask 2 uses nine fine-grained evasion categories. The authors propose CAMSR-CoT, a…

 Co-authors here

9 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 1 time (of the 149,439 papers whose bibliographies we read).

Updated

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