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Chenhao Wang

4 papers hereh-index 8275 citations25 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2

Across the 2 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL4
same name
  • Chenhao Wang — 7 papers, h 3
  • Chenhao Wang — 6 papers, h 4
  • Chenhao Wang — 2 papers, h 4
  • Chenhao Wang — 1 paper, h 0
  • Chenhao Wang — 1 paper, h 4
  • Chenhao Wang — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
collaborators

4 papers

cs.CL2026

Scalable Frequency- and Length-Aware Subdocument Deduplication for Large Language Model Pretraining

Hai Wang, Chenhao Wang, Qifeng Cai +6

Large-scale pretraining corpora contain substantial duplicate content. Although document-level deduplication is widely used, removing subdocument-level redundancy remains challengi…

cs.CL2026

Hy-MT2: A Family of Fast, Efficient and Powerful Multilingual Translation Models in the Wild

Mao Zheng, Zheng Li, Tao Chen +10

Hy-MT2 is a family of fast-thinking multilingual translation models designed for complex real-world scenarios. It includes three model sizes: 1.8B, 7B, and 30B-A3B (MoE), all of wh…

cs.CL2025

Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought

Tencent Hunyuan Team, Ao Liu, Botong Zhou +248

As Large Language Models (LLMs) rapidly advance, we introduce Hunyuan-TurboS, a novel large hybrid Transformer-Mamba Mixture of Experts (MoE) model. It synergistically combines Mam…

cs.CL2024

LINKED: Eliciting, Filtering and Integrating Knowledge in Large Language Model for Commonsense Reasoning

Jiachun Li, Pengfei Cao, Chenhao Wang +6

Large language models (LLMs) sometimes demonstrate poor performance on knowledge-intensive tasks, commonsense reasoning is one of them. Researchers typically address these issues b…

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