---
title: "Who cites David Evans — 190 papers of our library"
description: "190 papers of the Elamur Research library cite the works of David Evans, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/david-evans/cited-by/"
---
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# Who cites David Evans

190 citations of their works from 190 papers of our library (of the 149,439 whose bibliographies we read) · 25 with a page here, the most cited first · [← David Evans](https://md.research.elamur.ai/free/en/authors/david-evans/)

1. [**A Survey of Data Augmentation Approaches for NLP arXiv:2105.03075**Steven Y. Feng, Varun Gangal, Jason Wei, et al.*2021 · 940 citations*](https://md.research.elamur.ai/free/en/papers/feng-2021-survey-data-augmentation-approaches-nlp/)
2. [**Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment arXiv:2308.05374**Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li*2023 · 223 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-trustworthy-llms-survey-guideline-evaluating/)
3. **[Machine Unlearning of Pre-trained Large Language Models](https://md.research.elamur.ai/free/en/papers/yao-2024-machine-unlearning-pre-trained-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jin Yao, Eli Chien, Minxin Du, et al.*2024 · 86 citations*
4. [**Reviewing Scientific Papers for Critical Problems With Reasoning LLMs: Baseline Approaches and Automatic Evaluation arXiv:2505.23824**Tianmai M. Zhang, Neil F. Abernethy*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-reviewing-scientific-papers-critical-problems/)
5. **[Detecting Training Data of Large Language Models via Expectation Maximization](https://md.research.elamur.ai/free/en/papers/kim-2026-detecting-training-data-large-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Gyuwan Kim, Yang Li, Evangelia Spiliopoulou, et al.*2026 · 5 citations*
6. **[STReasoner: Empowering LLMs for Spatio-Temporal Reasoning in Time Series via Spatial-Aware Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/ni-2026-streasoner-empowering-llms-spatio-temporal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Juntong Ni, Shiyu Wang, Qi He, et al.*2026 · 3 citations*
7. **[Neural Breadcrumbs: Membership Inference Attacks on LLMs Through Hidden State and Attention Pattern Analysis](https://md.research.elamur.ai/free/en/papers/makhija-2026-neural-breadcrumbs-membership-inference-attacks/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Disha Makhija, Manoj Ghuhan Arivazhagan, Vinayshekhar Bannihatti Kumar, et al.*2026 · 2 citations*
8. **[Do LLMs Really Memorize Personally Identifiable Information? Revisiting PII Leakage with a Cue-Controlled Memorization Framework](https://md.research.elamur.ai/free/en/papers/luo-2026-do-llms-really-memorize-personally/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyu Luo, Yiyi Chen, Qiongxiu Li, et al.*2026 · 1 citation*
9. **[Hey, That's My Data! Token-Only Dataset Inference in Large Language Models](https://md.research.elamur.ai/free/en/papers/xiong-2026-hey-that-s-my-data/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chen Xiong, Zihao Wang, Rui Zhu, et al.*2026 · 1 citation*
10. **[Image Corruption-Inspired Membership Inference Attacks against Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/wu-2026-image-corruption-inspired-membership-inference/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zongyu Wu, Minhua Lin, Zhiwei Zhang, et al.*2026 · 1 citation*
11. **[MALTO at SVELA: A Specific-Attention-Head Approach for Membership Inference Attacks in LLMs Unlearning Evaluation](https://md.research.elamur.ai/free/en/papers/munis-2026-malto-svela-specific-attention-head/) [Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop](https://md.research.elamur.ai/free/en/venues/evalita/)**Evren A. Munis, Mattia Sabato, Erfan Bayat, et al.*2026 · 1 citation*
12. **[Optimizing Multilingual LLMs via Federated Learning: A Study of Client Language Composition](https://md.research.elamur.ai/free/en/papers/sant-2026-optimizing-multilingual-llms-federated-learning/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aleix Sant, Jordi Luque, Carlos Escolano*2026 · 1 citation*
13. **[Are LLM Benchmarks Already Contaminated? A Systematic Review of Contamination Detection Methods](https://md.research.elamur.ai/free/en/papers/nourbakhsh-2026-are-llm-benchmarks-already-contaminated/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Erfan Nourbakhsh, Mohammad Sadegh Sirjani, Amir Mousavi, et al.*2026*
14. **[Black-Box Membership Inference Attacks for Video Training Data in Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-black-box-membership-inference-attacks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinrui Wang, Zhenfeng Gao, Wendan Wang, et al.*2026*
15. **[CheckMIABench: Firm Foundations For Membership Inference Attacks on Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-checkmiabench-firm-foundations-membership-inference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jeffrey George Wang, Jason Wang, Marvin Li, et al.*2026*
16. **[Detecting Non-Membership in LLM Training Data via Rank Correlations](https://md.research.elamur.ai/free/en/papers/shetty-2026-detecting-non-membership-llm-training/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Pranav Shetty, Mirazul Haque, Zhiqiang Ma, et al.*2026*
17. **[EL-MIA: Quantifying Membership Inference Risks of Sensitive Entities in LLMs](https://md.research.elamur.ai/free/en/papers/satvaty-2026-el-mia-quantifying-membership-inference/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Ali Satvaty, Suzan Verberne, Fatih Turkmen*2026*
18. **[FedPAGR: Federated Prototype Alignment via Geometric Refinement for Heterogeneous Architectures](https://md.research.elamur.ai/free/en/papers/prasad-2026-fedpagr-federated-prototype-alignment-geometric/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kris Prasad, Md Abdullah Al Hafiz Khan*2026*
19. **[Lexical Popularity: Quantifying the Impact of Pre-training for LLM Performance](https://md.research.elamur.ai/free/en/papers/ruzzetti-2026-lexical-popularity-quantifying-impact-pre/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Elena Sofia Ruzzetti, Fabio Massimo Zanzotto, Tommaso Caselli*2026*
20. **[LLMSurgeon: Diagnosing Data Mixture of Large Language Models](https://md.research.elamur.ai/free/en/papers/luo-2026-llmsurgeon-diagnosing-data-mixture-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaxin Luo, Jiacheng Cui, Xiaohan Zhao, et al.*2026*
21. [**Obscuring Data Contamination Through Translation: Evidence from Arabic Corpora arXiv:2601.14994**Chaymaa Abbas, Nour Shamaa, Mariette Awad*2026*](https://md.research.elamur.ai/free/en/papers/abbas-2026-obscuring-data-contamination-through-translation/)
22. **[PDR: A Plug-and-Play Positional Decay Framework for LLM Pre-training Data Detection](https://md.research.elamur.ai/free/en/papers/liu-2026-pdr-plug-play-positional-decay/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinhan Liu, Yibo Yang, Ruiying Lu, et al.*2026*
23. **[Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation](https://md.research.elamur.ai/free/en/papers/ma-2026-private-seeds-public-llms-realistic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qian Ma, Sarah Rajtmajer*2026*
24. **[Safe-FedLLM: Delving into the Safety of Federated Large Language Models](https://md.research.elamur.ai/free/en/papers/tao-2026-safe-fedllm-delving-into-safety/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingxiang Tao, Yu Tian, Wenxuan Tu, et al.*2026*
25. **[SecureGate: Learning When to Reveal PII Safely via Token-Gated Dual-Adapters for Federated LLMs](https://md.research.elamur.ai/free/en/papers/shaaban-2026-securegate-learning-when-reveal-pii/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohamed Shaaban, Mohamed Elmahallawy*2026*

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

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