--- title: "Who cites Junxian Guo — 149 papers of our library" description: "149 papers of the Elamur Research library cite the works of Junxian Guo, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/junxian-guo/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/junxian-guo/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Junxian Guo](https://md.research.elamur.ai/free/en/authors/junxian-guo/) / cited by # Who cites Junxian Guo 170 citations of their works from 149 papers of our library (of the 149,439 whose bibliographies we read) · 20 with a page here, the most cited first · [← Junxian Guo](https://md.research.elamur.ai/free/en/authors/junxian-guo/) 1. [**Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention arXiv:2502.11089**Jingyang Yuan, Huazuo Gao, Damai Dai, et al.*2025 · 142 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2025-native-sparse-attention-hardware/) 2. [**XAttention: Block Sparse Attention with Antidiagonal Scoring arXiv:2503.16428**Ruyi Xu, Guangxuan Xiao, Haofeng Huang, et al.*2025 · 59 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-xattention-block-sparse-attention-antidiagonal/) 3. [**A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond arXiv:2503.21614**Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.*2025 · 55 citations*](https://md.research.elamur.ai/free/en/papers/qu-2025-survey-efficient-reasoning-large-reasoning/) 4. [**Kimi Linear: An Expressive, Efficient Attention Architecture arXiv:2510.26692**Kimi Team, Yu Zhang, Zongyu Lin, et al.*2025 · 51 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-linear-expressive-efficient/) 5. [**MiniCPM4: Ultra-Efficient LLMs on End Devices arXiv:2506.07900**MiniCPM Team, Chaojun Xiao, Yuxuan Li, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/minicpm-team-2025-minicpm4-ultra-efficient-llms/) 6. **[Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-locate-steer-improve-practical-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hengyuan Zhang, Zhihao Zhang, Ercong Nie, et al.*2026 · 9 citations* 7. **[HybridKV: Hybrid KV Cache Compression for Efficient Multimodal Large Language Model Inference](https://md.research.elamur.ai/free/en/papers/zeng-2026-hybridkv-hybrid-kv-cache-compression/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bowen Zeng, Feiyang Ren, Jun Zhang, et al.*2026 · 4 citations* 8. **[CAFE: Retrieval Head-based Coarse-to-Fine Information Seeking to Enhance Multi-Document QA Capability](https://md.research.elamur.ai/free/en/papers/peng-2025-cafe-retrieval-head-based-coarse/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Han Peng, Jinhao Jiang, Zican Dong, et al.*2025 · 4 citations* 9. **[Focus-dLLM: Accelerating Long-Context Diffusion LLM Inference via Confidence-Guided Context Focusing](https://md.research.elamur.ai/free/en/papers/long-2026-focus-dllm-accelerating-long-context/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingkun Long, Yushi Huang, Shihao Bai, et al.*2026 · 2 citations* 10. **[ART: Attention Replacement Technique to Improve Factuality in LLMs](https://md.research.elamur.ai/free/en/papers/luo-2026-art-attention-replacement-technique-improve/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziqin Luo, Yihao Quan, Xiaofeng Zhang, et al.*2026 · 1 citation* 11. **[From Static Inference to Dynamic Interaction: A Survey of Streaming Large Language Models](https://md.research.elamur.ai/free/en/papers/tong-2026-static-inference-dynamic-interaction-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junlong Tong, Zilong Wang, YuJie Ren, et al.*2026 · 1 citation* 12. **[From Logical to Computational Sparsity: Structure-Aware Block-Sparse Attention for Long-Code Completion](https://md.research.elamur.ai/free/en/papers/wang-2026-logical-computational-sparsity-structure-aware/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanli Wang, Yanlin Wang, Bowen Zhang, et al.*2026* 13. **[Latent-Condensed Transformer for Efficient Long Context Modeling](https://md.research.elamur.ai/free/en/papers/you-2026-latent-condensed-transformer-efficient-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zeng You, Yaofo Chen, Qiuwu Chen, et al.*2026* 14. **[MATCH: Modulating Attention via In-Context Retrieval for Long-Context Transformers](https://md.research.elamur.ai/free/en/papers/ma-2026-match-modulating-attention-context-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Linrui Ma, Chun Hei Lo, Xinyu Wang, et al.*2026* 15. **[Question Tells You Where the Answer Is: Intention-aware Long-Context KV Cache Compression](https://md.research.elamur.ai/free/en/papers/zhao-2026-question-tells-you-where-answer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liang Zhao, Xiaocheng Feng, Weihong Zhong, et al.*2026* 16. **[ReFreeKV: Towards Threshold-Free KV Cache Compression](https://md.research.elamur.ai/free/en/papers/ni-2026-refreekv-threshold-free-kv-cache/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuanfan Ni, Liyan Xu, Chenyang Lyu, et al.*2026* 17. **[RoBSA: RoPE-based Blockwise Sparse Multi-head Latent Attention](https://md.research.elamur.ai/free/en/papers/shi-2026-robsa-rope-based-blockwise-sparse/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyu Shi, Kairong Luo, Zhen Zheng, et al.*2026* 18. **[RRAtention: Dynamic Block Sparse Attention via Per-Head Round-Robin Shifts for Long-Context Inference](https://md.research.elamur.ai/free/en/papers/liu-2026-rratention-dynamic-block-sparse-attention/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Siran Liu, Guoxia Wang, Sa Wang, et al.*2026* 19. **[S2O: Early Stopping for Sparse Attention via Online Permutation](https://md.research.elamur.ai/free/en/papers/zhang-2026-s2o-early-stopping-sparse-attention/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Zhang, Songwei Liu, Chenqian Yan, et al.*2026* 20. **[Temporal Token Matters: Investigating and Interpreting the Consistency of Temporal Ordering in Large Language Models](https://md.research.elamur.ai/free/en/papers/yang-2026-temporal-token-matters-investigating-interpreting/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhen Yang, Xinyue Zhang, Ping Jian, et al.*2026* 129 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/junxian-guo/) — Junxian Guo