---
title: "Who cites Yuhang Wu — 5 papers of our library"
description: "5 papers of the Elamur Research library cite the works of Yuhang Wu, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/yuhang-wu/cited-by/"
---
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# Who cites Yuhang Wu

5 citations of their works from 5 papers of our library (of the 149,439 whose bibliographies we read) · 5 with a page here, the most cited first · [← Yuhang Wu](https://md.research.elamur.ai/free/en/authors/yuhang-wu/)

1. **[Psyche-R1: Towards Reliable Psychological LLMs through Unified Empathy, Expertise, and Reasoning](https://md.research.elamur.ai/free/en/papers/dai-2026-psyche-r1-reliable-psychological-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chongyuan Dai, Jinpeng Hu, Hongchang Shi, et al.*2026 · 8 citations*
2. **[PDTrim: Targeted Pruning for Prefill-Decode Disaggregation in Inference](https://md.research.elamur.ai/free/en/papers/zhang-2026-pdtrim-targeted-pruning-prefill-decode/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Zhang, Lyu Mengsi, Zhuo Chen, et al.*2026 · 6 citations*
3. **[TrimTokenator: Towards Adaptive Visual Token Pruning for Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-trimtokenator-adaptive-visual-token-pruning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Zhang, Lyu Mengsi, Chenrui He, et al.*2026 · 6 citations*
4. **[Not All Directions Matter: Towards Structured and Task-Aware Low-Rank Model Adaptation](https://md.research.elamur.ai/free/en/papers/xiao-2026-not-all-directions-matter-structured/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xi Xiao, Chenrui Ma, Yunbei Zhang, et al.*2026 · 3 citations*
5. **[Tailoring Memory Granularity for Multi-Hop Reasoning over Long Contexts](https://md.research.elamur.ai/free/en/papers/qing-2026-tailoring-memory-granularity-multi-hop/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Peijun Qing, Xingjian Diao, Chiyu Ma, et al.*2026 · 3 citations*
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