---
title: "Who cites Ligeng Zhu — 342 papers of our library"
description: "342 papers of the Elamur Research library cite the works of Ligeng Zhu, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/ligeng-zhu/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/ligeng-zhu/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Ligeng Zhu](https://md.research.elamur.ai/free/en/authors/ligeng-zhu/) / cited by

# Who cites Ligeng Zhu

364 citations of their works from 342 papers of our library (of the 149,439 whose bibliographies we read) · 22 with a page here, the most cited first · [← Ligeng Zhu](https://md.research.elamur.ai/free/en/authors/ligeng-zhu/)

1. **[EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks](https://md.research.elamur.ai/free/en/papers/tan-2019-efficientnet-rethinking-model-scaling-convolutional/) [International Conference on Machine Learning (ICML)](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/)**Mingxing Tan, Quoc V. Le*2019 · 5,416 citations*
2. **[Efficient Transformers: A Survey](https://md.research.elamur.ai/free/en/papers/tay-2020-efficient-transformers-survey/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Yi Tay, Mostafa Dehghani, Dara Bahri, et al.*2020 · 1,539 citations*
3. **[Progressive Differentiable Architecture Search: Bridging the Depth Gap between Search and Evaluation](https://md.research.elamur.ai/free/en/papers/chen-2019-progressive-differentiable-architecture-search-bridging/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Xin Chen, Lingxi Xie, Jun Wu, et al.*2019 · 732 citations*
4. **[SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning](https://md.research.elamur.ai/free/en/papers/wang-2020-spatten-efficient-sparse-attention-architecture/) [Proceedings - International Symposium on High-Performance Computer Architecture/Proceedings](https://md.research.elamur.ai/free/en/venues/proceedings-international-symposium-on-high-performance-computer-architecture/)**Hanrui Wang, Zhekai Zhang, Song Han*2020 · 534 citations*
5. **[HAT: Hardware-Aware Transformers for Efficient Natural Language Processing](https://md.research.elamur.ai/free/en/papers/wang-2020-hat-hardware-aware-transformers-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanrui Wang, Zhanghao Wu, Zhijian Liu, et al.*2020 · 294 citations*
6. [**Once-for-All: Train One Network and Specialize it for Efficient Deployment arXiv:1908.09791**Han Cai, Chuang Gan, Tianzhe Wang, et al.*2019 · 252 citations*](https://md.research.elamur.ai/free/en/papers/cai-2019-once-all-train-one-network/)
7. **[Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces](https://md.research.elamur.ai/free/en/papers/yang-2024-thinking-space-multimodal-large-language/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Jihan Yang, Shusheng Yang, Anjali W. Gupta, et al.*2024 · 182 citations*
8. **[Efficient Methods for Natural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/treviso-2023-efficient-methods-natural-language-processing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Marcos Treviso, Ji-Ung Lee, Tianchu Ji, et al.*2023 · 145 citations*
9. **[Video Compression Commander: Plug-and-Play Inference Acceleration for Video Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2025-video-compression-commander-plug-play/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xuyang Liu, Yiyu Wang, Junpeng Ma, et al.*2025 · 16 citations*
10. **[Too Many Frames, Not All Useful: Efficient Strategies for Long-Form Video QA](https://md.research.elamur.ai/free/en/papers/park-2026-too-many-frames-not-all/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Jongwoo Park, Kanchana Ranasinghe, Kumara Kahatapitiya, et al.*2026 · 13 citations*
11. **[Audio-centric Video Understanding Benchmark without Text Shortcut](https://md.research.elamur.ai/free/en/papers/yang-2025-audio-centric-video-understanding-benchmark/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yudong Yang, Jimin Zhuang, Guangzhi Sun, et al.*2025 · 10 citations*
12. **[SpecVLM: Enhancing Speculative Decoding of Video LLMs via Verifier-Guided Token Pruning](https://md.research.elamur.ai/free/en/papers/ji-2025-specvlm-enhancing-speculative-decoding-video/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yicheng Ji, Jun Zhang, Heming Xia, et al.*2025 · 10 citations*
13. **[VideoPro: Adaptive Program Reasoning for Long Video Understanding](https://md.research.elamur.ai/free/en/papers/li-2026-videopro-adaptive-program-reasoning-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenglin Li, Feng Han, Yikun Wang, et al.*2026 · 6 citations*
14. **[INFACT: A Diagnostic Benchmark for Induced Faithfulness and Factuality Hallucinations in Video-LLMs](https://md.research.elamur.ai/free/en/papers/yangjunqi-2026-infact-diagnostic-benchmark-induced-faithfulness/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yangjunqi, Yuecong Min, Jie Zhang, et al.*2026 · 5 citations*
15. **[BLEnD-Vis: Benchmarking Multimodal Cultural Understanding in Vision Language Models](https://md.research.elamur.ai/free/en/papers/tan-2026-blend-vis-benchmarking-multimodal-cultural/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Bryan Chen Zhengyu Tan, Weihua Zheng, Zhengyuan Liu, et al.*2026 · 2 citations*
16. **[Cross-layer Attention Sharing for Pre-trained Large Language Models](https://md.research.elamur.ai/free/en/papers/mu-2026-cross-layer-attention-sharing-pre/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Yongyu Mu, Yuzhang Wu, Yuchun Fan, et al.*2026 · 2 citations*
17. **[USB: A COMPREHENSIVE AND UNIFIED SAFETY EVALUATION BENCHMARK FOR MULTIMODAL LARGE LANGUAGE MODELS](https://md.research.elamur.ai/free/en/papers/zheng-2026-usb-comprehensive-unified-safety-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Baolin Zheng, Guanlin Chen, Qingyang Teng, et al.*2026 · 1 citation*
18. **[A Survey of Large Models in Sports](https://md.research.elamur.ai/free/en/papers/xu-2026-survey-large-models-sports/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yichen Xu, Jianzhe Ma, Chuhan Wang, et al.*2026*
19. **[HowToNarrate: A General-Domain Benchmark for Synchronized Video Narration with External Knowledge](https://md.research.elamur.ai/free/en/papers/wang-2026-howtonarrate-general-domain-benchmark-synchronized/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xueyan Wang, Dingyi Yang, Qin Jin*2026*
20. **[Minimal Clips, Maximum Salience: Long Video Summarization via Key Moment Extraction](https://md.research.elamur.ai/free/en/papers/pennec-2026-minimal-clips-maximum-salience-long/) [International Workshop on Spoken Dialogue System Technology](https://md.research.elamur.ai/free/en/venues/iwsds/)**Galann Pennec, Zhengyuan Liu, Nicholas Asher, et al.*2026*
21. **[Scaling Law for Multimodal Large Language Model Supervised Fine-Tuning](https://md.research.elamur.ai/free/en/papers/zhang-2026-scaling-law-multimodal-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**YiFan Zhang, Tao Yu, Feng Li, et al.*2026*
22. **[VIGiA: Instructional Video Guidance via Dialogue Reasoning and Retrieval](https://md.research.elamur.ai/free/en/papers/silva-2026-vigia-instructional-video-guidance-dialogue/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Diogo Glória-Silva, David Semedo, Joao Magalhaes*2026*

320 more citing papers of our library have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/authors/ligeng-zhu/) — Ligeng Zhu