---
title: "Who cites Timothy Lillicrap — page 3"
description: "3,750 papers of the Elamur Research library cite the works of Timothy Lillicrap, found in their bibliographies · page 3 of 3 · 201–221; the most cited…"
canonical: "https://research.elamur.ai/free/en/authors/timothy-lillicrap/cited-by/page/3/"
---
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# Who cites Timothy Lillicrap

3,990 citations of their works from 3,750 papers of our library (of the 140,884 whose bibliographies we read) · 221 with a page here, the most cited first · page 3 of 3 · 201–221 · [← Timothy Lillicrap](https://md.research.elamur.ai/free/en/authors/timothy-lillicrap/)

[← prev](https://md.research.elamur.ai/free/en/authors/timothy-lillicrap/cited-by/page/2/) [1](https://md.research.elamur.ai/free/en/authors/timothy-lillicrap/cited-by/) [2](https://md.research.elamur.ai/free/en/authors/timothy-lillicrap/cited-by/page/2/) **3**

201. [**Corpus and Baselines for Distinguishing Authentic, AI-Generated, and AI-Enhanced Resumes**Andrea Loizidou, Anshu Kiran Sharma, Adrian Esquivel, et al.*2026*](https://md.research.elamur.ai/free/en/papers/loizidou-2026-corpus-baselines-distinguishing-authentic-ai/)
202. [**Cultural and Knowledge Biases in LLMs through the Lens of Entity-Aware Machine Translation**Lu Xu, Luca Moroni, Roberto Navigli*2026*](https://md.research.elamur.ai/free/en/papers/xu-2026-cultural-knowledge-biases-llms-through/)
203. [**Do Multimodal LLMs Understand Order? Measuring the Fragility of Multimodal Reasoning under Input Order Perturbations**Sheng-Lun Wei, Yu-Ling Liao, Hen-Hsen Huang, et al.*2026*](https://md.research.elamur.ai/free/en/papers/wei-2026-do-multimodal-llms-understand-order/)
204. [**GhostWriter: Hidden AI-Generated Texts over Multiple Languages, Domains and Generators**Manuel Schaaf, Kevin Bönisch, Alexander Mehler*2026*](https://md.research.elamur.ai/free/en/papers/schaaf-2026-ghostwriter-hidden-ai-generated-texts/)
205. [**HEBATRON: A Hebrew-Specialized Open-Weight Mixture-of-Experts Language Model**Noam Kayzer, Dan Revital, Ori Bar Joseph, et al.*2026*](https://md.research.elamur.ai/free/en/papers/kayzer-2026-hebatron-hebrew-specialized-open-weight/)
206. [**HotelCheckSpan: A Benchmark Dataset for LLM Faithfulness**Patricia Schmidtova, Ondrej Dusek, Saad Mahamood*2026*](https://md.research.elamur.ai/free/en/papers/schmidtova-2026-hotelcheckspan-benchmark-dataset-llm-faithfulness/)
207. [**IndigiEval: Evaluating LLMs in North American Indigenous Languages**Julia Mainzinger, Jacqueline Brixey*2026*](https://md.research.elamur.ai/free/en/papers/mainzinger-2026-indigieval-evaluating-llms-north-american/)
208. [**Is AI Catching Up to Human Expression? Exploring Emotion, Personality, Authorship, and Linguistic Style in English and Arabic with Six Large Language Models**Nasser A Alsadhan*2026*](https://md.research.elamur.ai/free/en/papers/alsadhan-2026-ai-catching-up-human-expression/)
209. [**Merge and Conquer: Instructing Multilingual Models by Adding Target Language Weights**Eneko Valero, Maria Ribalta i Albado, Oscar Sainz, et al.*2026*](https://md.research.elamur.ai/free/en/papers/valero-2026-merge-conquer-instructing-multilingual-models/)
210. [**MQM Re-Annotation: A Technique for Collaborative Evaluation of Machine Translation**Parker Riley, Daniel Deutsch, Mara Finkelstein, et al.*2026*](https://md.research.elamur.ai/free/en/papers/riley-2026-mqm-re-annotation-technique-collaborative/)
211. [**Multi-Agent Debate for Machine Translation: A Case Study on English-Japanese Translation**Zhan Shen, Jason Naradowsky, Xiaotian Wang, et al.*2026*](https://md.research.elamur.ai/free/en/papers/shen-2026-multi-agent-debate-machine-translation/)
212. [**Multimodal LLMs Do Not Compose Skills Optimally across Modalities**Paula Ontalvilla, Aitor Ormazabal, Gorka Azkune*2026*](https://md.research.elamur.ai/free/en/papers/ontalvilla-2026-multimodal-llms-do-not-compose/)
213. [**Push and Pull: Training Sentence Encoders with Contrastive Losses for Distance-Based Multi-Label Text Classification**Jens Van Nooten, Andriy Kosar*2026*](https://md.research.elamur.ai/free/en/papers/nooten-2026-push-pull-training-sentence-encoders/)
214. [**Seeing the Other Side: Diagnostic Tasks for Viewpoint Reasoning in Vision–Language Models**Makoto Takenaka, Hitomi Yanaka*2026*](https://md.research.elamur.ai/free/en/papers/takenaka-2026-seeing-other-side-diagnostic-tasks/)
215. [**Sentiment Analysis and Language Models for Kwanyama**Ndapa Nakashole*2026*](https://md.research.elamur.ai/free/en/papers/nakashole-2026-sentiment-analysis-language-models-kwanyama/)
216. [**ViX-Ray: A Vietnamese Chest X-Ray Dataset for Vision-Language Models**Duy Vu Minh Nguyen, Chinh Thanh Truong, Trần Hoàng Phúc, et al.*2026*](https://md.research.elamur.ai/free/en/papers/nguyen-2026-vix-ray-vietnamese-chest-x/)
217. [**When Similar Means Different: Evaluating LLMs on Arabic–Hebrew Cognates**Junhong Liang, Noor Abo Mokh, Bashar Alhafni*2026*](https://md.research.elamur.ai/free/en/papers/liang-2026-similar-means-different-evaluating-llms/)
218. [**Embodied Intelligence Systems Based on Large Models: A Survey (基于大模型的具身智能系统综述)**Wensheng Wang (王文晟), Ning Tan (谭宁), Kai Huang (黄凯), et al.*2025*](https://md.research.elamur.ai/free/en/papers/wang-2025-embodied-intelligence-systems/)
219. [**Sarc7: Evaluating Sarcasm Detection and Generation with Seven Types and Emotion-Informed Techniques**Lang Xiong, Raina Gao, Alyssa Jeong*2025*](https://md.research.elamur.ai/free/en/papers/xiong-2025-sarc7-evaluating-sarcasm-detection-generation/)
220. [**Survey of Tool Use in Large Language Models (大语言模型的工具使用综述)**Yining Zheng (郑逸宁), Zhen Yu (余镇), Bufan Li (李不凡), et al.*2025*](https://md.research.elamur.ai/free/en/papers/zheng-2025-tool-use-large/)
221. [**Leveraging BERT Language Model for Arabic Long Document Classification**Muhammad AL-Qurishi*2023*](https://md.research.elamur.ai/free/en/papers/al-qurishi-2023-leveraging-bert-language-model-arabic/)

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3,529 more citing papers of our library have no page here yet.

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