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Shuangyong Song

Shuangyong Song has 6 papers in our library, in 2026, most of them on Reasoning, Machine translation, Language models & pretraining; often with Xuelong Li, Yongxiang Li, Shiquan Wang.

6 papers in our library · 2026

OpenAlex · h-index 0 · 8 works · 0 citations OpenAlex, 2026-10-14

📄 6 works in our library · 🔗 Cited 1 time in our library · ⭐ Paper Stars ranking: #12688

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 · 8 paperscurrent🏢China TelecomChangsha · China2026 · 1 papercurrent

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 8The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 6 worksArts and Humanities · 6 worksComputer Science · 6 worksLanguage and Linguistics · 6 worksExperimental and Cognitive Psychology · 1 workPsychology · 1 workComputer Vision and Pattern Recognition · 1 workInformation Systems · 1 work

🧭 Topics 4Research subjects and languages the work is about.Language models & pretraining · 1 workSentiment & emotion · 1 workReasoning · 2 worksMachine translation · 1 work

 Works by year

2020s

20266 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. CEMT:Controllable Element-Oriented Machine Translation via Structured Linguistic Reasoning (2026)
    LLM-based translators often mishandle small but critical pieces of input: URLs, handles, HTML tags and emojis that must be copied exactly, and idioms, slang or culture-bound terms that need careful adaptation.
  3. Hallucinations as Orthogonal Noise: Inference-Time Manifold Alignment via Dynamic Contextual Orthogonalization (2026)
    The paper addresses LLM hallucinations, where outputs contradict the given context or logical constraints.
  4. Table-R1: Region-based Reinforcement Learning for Table Understanding (2026)
    Large language models still have difficulty answering questions over tables because answers depend on how rows and columns relate.
  5. 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:
  6. 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

12 of 23 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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