🧑‍🔬 Qing Gu

🏛️ Affiliations

🎓Nanjing UniversityNanjing · China2000–2026 · 86 paperscurrent🔬State Key Laboratory of New Technology of Computer SoftwareNanjing · China2009–2020 · 5 papers🎓University of AizuFukushima · Japan2009–2010 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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. LongRecipe: Recipe for Efficient Long Context Generalization in Large Language Models (2025 · 16 citations)
   Large language models handle inputs poorly once these exceed the context length seen during pretraining. Continuing training on full-length sequences fixes this but is expensive, since attention cost grows quadratically with length. LongRecipe is a training framework that extends the context window without training…
2. Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMs (2025 · 10 citations)
   Decoder-only LLMs rely on causal attention. When sentence embeddings are extracted from them without fine-tuning, tokens near the start of the input cannot see later tokens. Prompt-based methods such as PromptEOL read the embedding from the final prompt token, but that token still inherits the skewed representations…
3. Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering (2025 · 8 citations)
   Large language models can produce sentence embeddings without any training data or fine-tuning: a prompt wraps the sentence, and the hidden state of the final token serves as the vector.

All works

5 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. A Unified Target-Oriented Sequence-to-Sequence Model for Emotion-Cause Pair Extraction ↗IEEE/ACM Transactions on Audio Speech and Language Processing · no summary yetZifeng Cheng et al.2021 · 70 citations
2. LongRecipe: Recipe for Efficient Long Context Generalization in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhiyuan Hu, Yuliang Liu, Jinman Zhao, et al.2025 · 16 citations
3. Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Yuchen Fu, Zifeng Cheng, Zhiwei Jiang, et al.2025 · 10 citations
4. Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time SteeringAnnual Meeting of the Association for Computational Linguistics (ACL)Zifeng Cheng, Zhonghui Wang, Yuchen Fu, et al.2025 · 8 citations
5. AEA: Adaptive Expert Allocation Improves Sentence Embeddings from Mixture-of-Experts LLM ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetShufan Yang et al.2026

🤝 Co-authors here

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

• Zhiwei Jiang ×3
• Yafeng Yin ×2
• Yuchen Fu ×2
• Zhonghui Wang ×2
• Zifeng Cheng ×2
• Anh Tuan Luu
• Bryan Hooi
• Jinman Zhao
• See-Kiong Ng
• Wei Shen
• Yan Wang
• Yuliang Liu

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) ×4: ACL 2025 ×3
• IEEE/ACM Transactions on Audio Speech and Language Processing

🔗 Cited by

Papers of our library cite their works 40 times (of the 149,439 papers whose bibliographies we read); 10 citing papers with a page here →.

Updated 30 October 2026

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