---
title: "Who cites Zhengxuan Wu — page 2 — 814 papers of our library"
description: "814 papers of the Elamur Research library cite the works of Zhengxuan Wu, found in their bibliographies · page 2 of 2 · 101–143; the most cited first."
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---
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# Who cites Zhengxuan Wu

1,098 citations of their works from 814 papers of our library (of the 149,439 whose bibliographies we read) · 143 with a page here, the most cited first · page 2 of 2 · 101–143 · [← Zhengxuan Wu](https://md.research.elamur.ai/free/en/authors/zhengxuan-wu/)

[← prev](https://md.research.elamur.ai/free/en/authors/zhengxuan-wu/cited-by/) [1](https://md.research.elamur.ai/free/en/authors/zhengxuan-wu/cited-by/) **2**

101. **[CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data](https://md.research.elamur.ai/free/en/papers/suarez-2026-commonlid-re-evaluating-state-art/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pedro Ortiz Suarez, Laurie Burchell, Catherine Arnett, et al.*2026 · 3 citations*
102. **[Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering](https://md.research.elamur.ai/free/en/papers/zhao-2026-denoising-concept-vectors-sparse-autoencoders/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haiyan Zhao, Xuansheng Wu, Fan Yang, et al.*2026 · 3 citations*
103. **[Steering Large Language Models for Machine Translation Personalization](https://md.research.elamur.ai/free/en/papers/scalena-2026-steering-large-language-models-machine/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Daniel Scalena, Gabriele Sarti, Arianna Bisazza, et al.*2026 · 3 citations*
104. **[VeriTaS: The First Dynamic Benchmark for Multimodal Automated Fact-Checking](https://md.research.elamur.ai/free/en/papers/rothermel-2026-veritas-first-dynamic-benchmark-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mark Rothermel, Marcus Kornmann, Marcus Rohrbach, et al.*2026 · 3 citations*
105. **[Comparing Human and Large Language Model Interpretation of Implicit Information](https://md.research.elamur.ai/free/en/papers/santis-2026-comparing-human-large-language-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Antonio De Santis, Tommaso Bonetti, Andrea Tocchetti, et al.*2026 · 2 citations*
106. **[Language of Thought Shapes Output Diversity in Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-language-thought-shapes-output-diversity/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shaoyang Xu, Wenxuan Zhang*2026 · 2 citations*
107. **[Latent Agents: A Post-Training Procedure for Internalized Multi-Agent Debate](https://md.research.elamur.ai/free/en/papers/yi-2026-latent-agents-post-training-procedure/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**John Seon Keun Yi, Aaron Mueller, Dokyun Lee*2026 · 2 citations*
108. **[RefusalBench: Generative Evaluation of Selective Refusal in Grounded Language Models](https://md.research.elamur.ai/free/en/papers/muhamed-2026-refusalbench-generative-evaluation-selective-refusal/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Aashiq Muhamed, Leonardo F. R. Ribeiro, Markus Dreyer, et al.*2026 · 2 citations*
109. **[AiraXiv: An AI-Driven Open-Access Platform for Human and AI Scientists](https://md.research.elamur.ai/free/en/papers/pan-2026-airaxiv-ai-driven-open-access/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junshu Pan, Panzhong Lu, Yixuan Weng, et al.*2026 · 1 citation*
110. **[Among Us: Measuring and Mitigating Malicious Contributions in Model Collaboration Systems](https://md.research.elamur.ai/free/en/papers/yang-2026-among-us-measuring-mitigating-malicious/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyuan Yang, Wenxuan Ding, Shangbin Feng, et al.*2026 · 1 citation*
111. **[Constructing Interpretable Features from Compositional Neuron Groups](https://md.research.elamur.ai/free/en/papers/shafran-2026-constructing-interpretable-features-compositional-neuron/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Or David Shafran, Atticus Geiger, Mor Geva*2026 · 1 citation*
112. **[Deciphering Cultural Representations in Large Language Models via Sparse Autoencoders](https://md.research.elamur.ai/free/en/papers/zou-2026-deciphering-cultural-representations-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenye Zou, Difan Jiao, Lijie Hu*2026 · 1 citation*
113. **[From Weights to Activations: Is Steering the Next Frontier of Adaptation?](https://md.research.elamur.ai/free/en/papers/ostermann-2026-weights-activations-is-steering-next/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Simon Ostermann, Daniil Gurgurov, Tanja Baeumel, et al.*2026 · 1 citation*
114. **[Mechanistic Interpretability Should Prioritize Feature Consistency in Sparse Autoencoders](https://md.research.elamur.ai/free/en/papers/song-2026-mechanistic-interpretability-should-prioritize-feature/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangchen Song, Aashiq Muhamed, Yujia Zheng, et al.*2026 · 1 citation*
115. **[Multi-component Causal Tracing in Large Language Models](https://md.research.elamur.ai/free/en/papers/yan-2026-multi-component-causal-tracing-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zirui Yan, Dennis Wei, Dmitriy A Katz, et al.*2026 · 1 citation*
116. **[Polynomial Expansion Rank Adaptation: Enhancing Low-Rank Fine-Tuning with High-Order Interactions](https://md.research.elamur.ai/free/en/papers/zhang-2026-polynomial-expansion-rank-adaptation-enhancing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenhao Zhang, Lin Mu, Li Ni, et al.*2026 · 1 citation*
117. **[Start Making Sense(s): A Developmental Probe of Attention Specialization Using Lexical Ambiguity](https://md.research.elamur.ai/free/en/papers/riviere-2026-start-making-sense-s-developmental/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Pamela D. Rivière, Sean Trott*2026 · 1 citation*
118. **[TinyAttack: Exploring Stylistic Vulnerabilities in Large Language Models](https://md.research.elamur.ai/free/en/papers/mamta-2026-tinyattack-exploring-stylistic-vulnerabilities-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mamta Mamta, Bogdan Grecu, Oana Cocarascu*2026 · 1 citation*
119. **[Towards a Diagnostic and Predictive Evaluation Methodology for Sequence Labeling Tasks](https://md.research.elamur.ai/free/en/papers/mellado-2026-diagnostic-predictive-evaluation-methodology-sequence/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Elena Alvarez-Mellado, Julio Gonzalo*2026 · 1 citation*
120. **[Why Steering Works: Toward a Unified View of Language Model Parameter Dynamics](https://md.research.elamur.ai/free/en/papers/xu-2026-why-steering-works-unified-view/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziwen Xu, Chenyan WU, Hengyu Sun, et al.*2026 · 1 citation*
121. **[A framework for analyzing concept representations in neural models](https://md.research.elamur.ai/free/en/papers/naowarat-2026-framework-analyzing-concept-representations-neural/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Burin Naowarat, Hao Tang, Sharon Goldwater*2026*
122. **[AICA-Bench: Holistically Examining the Capabilities of VLMs in Affective Image Content Analysis](https://md.research.elamur.ai/free/en/papers/she-2026-aica-bench-holistically-examining-capabilities/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dong She, Xianrong Yao, Liqun Chen, et al.*2026*
123. [**Are Arabic Benchmarks Reliable? QIMMA's Quality-First Approach to LLM Evaluation arXiv:2604.03395**Leen AlQadi, Ahmed Alzubaidi, Mohammed Alyafeai, et al.*2026*](https://md.research.elamur.ai/free/en/papers/alqadi-2026-arabic-benchmarks-reliable-qimma-s/)
124. **[Bears, all bears, and some bears. Language Constraints on Language Models' Inductive Inferences](https://md.research.elamur.ai/free/en/papers/padmanabhan-2026-bears-all-bears-some-bears/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sriram Padmanabhan, Siyuan Song, Kanishka Misra*2026*
125. **[BenchNavigator: A Discovery Interface for Comparing LLM Benchmarks](https://md.research.elamur.ai/free/en/papers/sokol-2026-benchnavigator-discovery-interface-comparing-llm/) [Workshop on Evaluating Evaluations (EvalEval)](https://md.research.elamur.ai/free/en/venues/evaleval/)**Anna Sokol, Inge Vejsbjerg, Elizabeth M. Daly, et al.*2026*
126. **[Compositional Meaning Representations in LLMs: a Critical Review of Probing Studies](https://md.research.elamur.ai/free/en/papers/marro-2026-compositional-meaning-representations-llms-critical/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Rémy Marro*2026*
127. **[Compositional Steering of Large Language Models with Steering Tokens](https://md.research.elamur.ai/free/en/papers/radevski-2026-compositional-steering-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gorjan Radevski, Kiril Gashteovski, Giwon Hong, et al.*2026*
128. **[Credal Concept Bottleneck Models for Epistemic–Aleatoric Uncertainty Decomposition](https://md.research.elamur.ai/free/en/papers/mukherjee-2026-credal-concept-bottleneck-models-epistemic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tanmoy Mukherjee, Thomas Bailleux, Pierre Marquis, et al.*2026*
129. **[DocPolarBERT: A Pre-trained Model for Document Understanding with Relative Polar Coordinate Encoding of Layout Structures](https://md.research.elamur.ai/free/en/papers/uthayasooriyar-2026-docpolarbert-pre-trained-model-document/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Benno Uthayasooriyar, Antoine Ly, Franck Vermet, et al.*2026*
130. **[FABLE: Fine-grained Fact Anchoring for Unstructured Model Editing](https://md.research.elamur.ai/free/en/papers/wang-2026-fable-fine-grained-fact-anchoring/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Peng Wang, Biyu Zhou, Xuehai Tang, et al.*2026*
131. **[FedReFT: Federated Representation Fine-Tuning with All-But-Me Aggregation](https://md.research.elamur.ai/free/en/papers/siddika-2026-fedreft-federated-representation-fine-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fatema Siddika, Md Anwar Hossen, Juan Pablo Munoz, et al.*2026*
132. **[From Insight to Action: A Novel Framework for Interpretability-Guided Data Selection in Large Language Models](https://md.research.elamur.ai/free/en/papers/shi-2026-insight-action-novel-framework-interpretability/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ling Shi, Xinwei Wu, Xiaohu Zhao, et al.*2026*
133. **[From Isolation to Entanglement: When Do Interpretability Methods Identify and Disentangle Known Concepts?](https://md.research.elamur.ai/free/en/papers/mueller-2026-isolation-entanglement-when-do-interpretability/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aaron Mueller, Andrew Lee, Shruti Joshi, et al.*2026*
134. **[From Narrow Unlearning to Emergent Misalignment in LLMs](https://md.research.elamur.ai/free/en/papers/mushtaq-2026-narrow-unlearning-emergent-misalignment-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Erum Mushtaq, Anil Ramakrishna, Satyapriya Krishna, et al.*2026*
135. **[G-HiRel: Enhancing the Adaption to Knowledge Updating for Large Language Model Reasoning](https://md.research.elamur.ai/free/en/papers/pan-2026-g-hirel-enhancing-adaption-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yudai Pan, Jiajie Hong, Tianzhe Zhao, et al.*2026*
136. **[LIBERTy: A Causal Framework for Benchmarking Concept-Based Explanations of LLMs with Structural Counterfactuals](https://md.research.elamur.ai/free/en/papers/toker-2026-liberty-causal-framework-benchmarking-concept/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Gilat Toker, Nitay Calderon, Ohad Amosy, et al.*2026*
137. **[Mechanistic Interpretability Meets Cognitive Linguistics: Modelling Locative Image Schemas in the Circuit Framework](https://md.research.elamur.ai/free/en/papers/proietti-2026-mechanistic-interpretability-meets-cognitive-linguistics/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mattia Proietti, Afra Alishahi, Grzegorz Chrupała, et al.*2026*
138. **[Model Directions, Not Words: Mechanistic Topic Models Using Sparse Autoencoders](https://md.research.elamur.ai/free/en/papers/zheng-2026-model-directions-not-words-mechanistic/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Carolina Zheng, Nicolas Beltran-Velez, Sweta Karlekar, et al.*2026*
139. **[OrthoEdit: Principled and Stable Knowledge Editing via Orthogonal Subspace Projection](https://md.research.elamur.ai/free/en/papers/qiao-2026-orthoedit-principled-stable-knowledge-editing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Shanbao Qiao, Xuebing Liu, Akshat Gupta, et al.*2026*
140. **[Output-Space Search: Targeting LLM Generations in a Frozen Encoder-Defined Output Space](https://md.research.elamur.ai/free/en/papers/materzok-2026-output-space-search-targeting-llm/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Tobias Materzok*2026*
141. **[Persona-Aware Evaluation of Cognitive Bias in LLMs: From Benchmark to Applied Decision-Making](https://md.research.elamur.ai/free/en/papers/yoshikawa-2026-persona-aware-evaluation-cognitive-bias/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Katsumasa Yoshikawa, Junya Takayama, Takato Yamazaki*2026*
142. **[TARE: Lightweight Token-Aware Representation Editing for Fine-tuning Transformer-like Models](https://md.research.elamur.ai/free/en/papers/wang-2026-tare-lightweight-token-aware-representation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yulong Wang, Siyu Zhao*2026*
143. **[The evolution of linguistic patterns in scientific writing in Portuguese: an analysis with NILC-Metrix (Evolução de Padrões Linguísticos na Escrita Científica em Português: Uma Análise com NILC-Metrix)](https://md.research.elamur.ai/free/en/papers/lobo-2026-evolucao-de-padroes-linguisticos-na/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Thiago Ruiz Lobo, Claudia Aparecida Martins*2026*

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