---
title: "Who cites Johannes Heidecke — page 2"
description: "3,808 papers of the Elamur Research library cite the works of Johannes Heidecke, found in their bibliographies · page 2 of 2 · 101–163; the most cited…"
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---
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# Who cites Johannes Heidecke

4,332 citations of their works from 3,808 papers of our library (of the 140,884 whose bibliographies we read) · 163 with a page here, the most cited first · page 2 of 2 · 101–163 · [← Johannes Heidecke](https://md.research.elamur.ai/free/en/authors/johannes-heidecke/)

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

101. [**Synthetic Function Demonstrations Improve Generation in Low-Resource Programming Languages**Nick McKenna, Xinnuo Xu, Jack Williams, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/mckenna-2026-synthetic-function-demonstrations-improve-generation/)
102. [**Team QUESPA System Submission for the IWSLT 2026 Dialectal and Low-resource Speech Translation Task**John E. Ortega, Rodolfo Joel Zevallos, Fabrício Carraro, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/ortega-2026-team-quespa-system-submission-iwslt/)
103. [**LCHAIM - Investigating Long Context Reasoning in Hebrew**Ehud Malul, Oriel Perets, Ziv Mor, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/malul-2025-lchaim-investigating-long-context-reasoning/)
104. [**A Dataset for Oral Reading in Young English Readers**Madison Rose, Michael Bennie, Valeria Pagliai, et al.*2026*](https://md.research.elamur.ai/free/en/papers/rose-2026-dataset-oral-reading-young-english/)
105. [**A Dialogue System for Second Language Learning with Dynamic Adaptation to In-Dialogue Difficulty Changes**Taku Morioka, Junya Takayama, Tomoyuki Kajiwara*2026*](https://md.research.elamur.ai/free/en/papers/morioka-2026-dialogue-system-second-language-learning/)
106. [**A Scalable Pipeline for Novelty Detection in Skill Extraction Using Large Language Models**Gian Seifert, Simon Clematide*2026*](https://md.research.elamur.ai/free/en/papers/seifert-2026-scalable-pipeline-novelty-detection-skill/)
107. [**A Single Model Ensemble Framework for Neural Machine Translation Using Pivot Translation**Seokjin Oh, Keonwoong Noh, Woohwan Jung*2026*](https://md.research.elamur.ai/free/en/papers/oh-2026-single-model-ensemble-framework-neural/)
108. [**Arabic Morphosyntactic Tagging and Dependency Parsing with Large Language Models**Mohamed Adel, Bashar Alhafni, Nizar Habash*2026*](https://md.research.elamur.ai/free/en/papers/adel-2026-arabic-morphosyntactic-tagging-dependency-parsing/)
109. [**Arabic Safety Alignment as Selective Refusal: An Empirical Study of SFT, DPO, and Guard Calibration**Mohamad Zbib, Ammar Mohanna*2026*](https://md.research.elamur.ai/free/en/papers/zbib-2026-arabic-safety-alignment-selective-refusal/)
110. [**ArabiGEE: A Hierarchical Taxonomy for Arabic Grammatical Error Explanation**Khaled Elhady, Omar Kallas, Nizar Habash, et al.*2026*](https://md.research.elamur.ai/free/en/papers/elhady-2026-arabigee-hierarchical-taxonomy-arabic-grammatical/)
111. [**AraDynFact: Dynamic Evaluation of Factual Knowledge in Arabic**Ignacio Iacobacci, Faroq Altam, Zhaozhi Qian, et al.*2026*](https://md.research.elamur.ai/free/en/papers/iacobacci-2026-aradynfact-dynamic-evaluation-factual-knowledge/)
112. [**Assessing Y-Axis Influence: Bias in Multimodal Language Models on Chart-to-Table Translation**Seok Hwan Song, Azher Ahmed Efat, Wallapak Tavanapong*2026*](https://md.research.elamur.ai/free/en/papers/song-2026-assessing-y-axis-influence-bias/)
113. [**Augmenting LLM Reasoning with Dynamic Notes Writing for Complex MultiHop QA**Rishabh Maheshwary, Masoud Hashemi, Khyati Mahajan, et al.*2026*](https://md.research.elamur.ai/free/en/papers/maheshwary-2026-augmenting-llm-reasoning-dynamic-notes/)
114. [**Beyond Simple Term Injection: Reasoning Models for Legal Translation in a Non-Dominant Language Variety**Paolo Di Natale, Elena Chiocchetti, Marlies Alber, et al.*2026*](https://md.research.elamur.ai/free/en/papers/natale-2026-beyond-simple-term-injection-reasoning/)
115. [**CAIT: A Syntactic Parsing Toolkit for Child–Adult InTeractions**Francesca Padovani, Xiulin Yang, Bastian Bunzeck, et al.*2026*](https://md.research.elamur.ai/free/en/papers/padovani-2026-cait-syntactic-parsing-toolkit-child/)
116. [**Can LLMs Faithfully Explain Themselves in Low-Resource Languages? A Case Study on Emotion Detection in Persian**Mobina Mehrazar, Mohammad Amin Yousefi, Parisa Beygi, et al.*2026*](https://md.research.elamur.ai/free/en/papers/mehrazar-2026-can-llms-faithfully-explain-themselves/)
117. [**Child-directed speech facilitates production, not comprehension, in BabyLMs**Bastian Bunzeck, Sina Zarrieß*2026*](https://md.research.elamur.ai/free/en/papers/bunzeck-2026-child-directed-speech-facilitates-production/)
118. [**ChildTalk: A Multi-Dialect Chinese Child Speech Corpus with Full-Length Child–Caregiver Conversations for Speech Recognition**Jiaming Zhou, Yujie Guo, Shiwan Zhao, et al.*2026*](https://md.research.elamur.ai/free/en/papers/zhou-2026-childtalk-multi-dialect-chinese-child/)
119. [**Common Sense vs. Morality: The Curious Case of Narrative Focus Bias in LLMs**Saugata Purkayastha, Pranav Kushare, Pragya Paramita Pal, et al.*2026*](https://md.research.elamur.ai/free/en/papers/purkayastha-2026-common-sense-vs-morality-curious/)
120. [**CRiT-QA: Evaluating Multi-hop Reasoning with Counterfactual Chains and Distractor Traps**Jungmin Yun, June Hyoung Kwon, Youngbin Kim*2026*](https://md.research.elamur.ai/free/en/papers/yun-2026-crit-qa-evaluating-multi-hop/)
121. [**Data-Centric Approach at the LoResMT 2026 Turkic Translation Challenge: Russian-Kyrgyz**Dmitry Novokshanov*2026*](https://md.research.elamur.ai/free/en/papers/novokshanov-2026-data-centric-approach-loresmt-2026/)
122. [**Detecting Hallucinations in Authentic LLM–Human Interactions**Yujie Ren, Niklas Gruhlke, Anne Lauscher*2026*](https://md.research.elamur.ai/free/en/papers/ren-2026-detecting-hallucinations-authentic-llm-human/)
123. [**Detecting Latin in Historical Books with Large Language Models: A Multimodal Benchmark**Yu Wu, Ke Shu, Jonas Fischer, et al.*2026*](https://md.research.elamur.ai/free/en/papers/wu-2026-detecting-latin-historical-books-large/)
124. [**DRInQ: Evaluating Conversational Implicature with Controlled Context Variation**Hirona Jacqueline Arai, Xiang Ren*2026*](https://md.research.elamur.ai/free/en/papers/arai-2026-drinq-evaluating-conversational-implicature-controlled/)
125. [**Evaluating the Effect of Question Wording Variations on Answer Consistency in Large Language Models**Junya Takayama, Masaya Ohagi, Tomoya Mizumoto, et al.*2026*](https://md.research.elamur.ai/free/en/papers/takayama-2026-evaluating-effect-question-wording-variations/)
126. [**Evaluation of Paralinguistic-Aware Spoken Dialogue Systems using Next-Utterance Classification**Kouki Miyazawa, Yoshinao Sato*2026*](https://md.research.elamur.ai/free/en/papers/miyazawa-2026-evaluation-paralinguistic-aware-spoken-dialogue/)
127. [**From Propositional to Perceptual Asymmetry: Extending FPO to Asymmetric Partial Information Dialogue**Yifan Zhu, Kyeongmin Rim, James Pustejovsky*2026*](https://md.research.elamur.ai/free/en/papers/zhu-2026-propositional-perceptual-asymmetry-extending-fpo/)
128. [**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/)
129. [**HistoryBankQA: Multilingual Temporal Question Answering on Historical Events**Biswadip Mandal, Anant Khandelwal, Manish Gupta*2026*](https://md.research.elamur.ai/free/en/papers/mandal-2026-historybankqa-multilingual-temporal-question-answering/)
130. [**HOTATE: A Japanese Dialogue Corpus Annotated with Responses of Private Thoughts and Public Statements**Yuko Toda, Daisuke Maekawa, Kota Manabe, et al.*2026*](https://md.research.elamur.ai/free/en/papers/toda-2026-hotate-japanese-dialogue-corpus-annotated/)
131. [**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/)
132. [**HybridCodeAuthorship: A Benchmark Dataset for Line-Level Code Authorship Detection**Luke S. Patterson, Li Wang, Adam Faulkner*2026*](https://md.research.elamur.ai/free/en/papers/patterson-2026-hybridcodeauthorship-benchmark-dataset-line-level/)
133. [**Identifying Imaging Follow-Up in Radiology Reports: A Comparative Analysis of Traditional ML and LLM Approaches**Namu Park, Giridhar Kaushik Ramachandran, Kevin Lybarger, et al.*2026*](https://md.research.elamur.ai/free/en/papers/park-2026-identifying-imaging-follow-up-radiology/)
134. [**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/)
135. [**Information Asymmetry across Language Varieties: A Case Study on Cantonese-Mandarin and Bavarian-German QA**Renhao Pei, Siyao Peng, Verena Blaschke, et al.*2026*](https://md.research.elamur.ai/free/en/papers/pei-2026-information-asymmetry-across-language-varieties/)
136. [**InstructSum: A Benchmark to Evaluate Instruction-Following Capability of Large Language Models in Summarization**Kosuke Nishida, Kyosuke Nishida, Itsumi Saito*2026*](https://md.research.elamur.ai/free/en/papers/nishida-2026-instructsum-benchmark-evaluate-instruction-following/)
137. [**Is Biomedical Specialization Still Worth It? Insights from Domain-Adaptive Language Modelling with a New French Health Corpus**Aidan Mannion, Cécile Macaire, Armand Violle, et al.*2026*](https://md.research.elamur.ai/free/en/papers/mannion-2026-is-biomedical-specialization-still-worth/)
138. [**Leveraging Digitized Newspapers to Collect Summarization Data in Low-Resource Languages**Noam Dahan, Omer Kidron, Gabriel Stanovsky*2026*](https://md.research.elamur.ai/free/en/papers/dahan-2026-leveraging-digitized-newspapers-collect-summarization/)
139. [**LLMs Out-of-the-Box Do Not Generate Context-Appropriate Word Order in Russian**Alina Shabaeva, John Frederick Bailyn, Owen Rambow*2026*](https://md.research.elamur.ai/free/en/papers/shabaeva-2026-llms-out-box-do-not/)
140. [**Meaning Over Morphology: A Multi-Metric Benchmark of LLMs for Bangla Dialect Translation**Soumik Deb Niloy, Subhey Sadi Rahman, Mahbub E Sobhani, et al.*2026*](https://md.research.elamur.ai/free/en/papers/niloy-2026-meaning-over-morphology-multi-metric/)
141. [**mSCoRe: A Multilingual and Scalable Benchmark for Skill-based Commonsense Reasoning**Nghia Trung Ngo, Franck Dernoncourt, Thien Huu Nguyen*2026*](https://md.research.elamur.ai/free/en/papers/ngo-2026-mscore-multilingual-scalable-benchmark-skill/)
142. [**Multilingual Target-Stance Extraction**Ethan Leigh Mines, Bonnie J. Dorr*2026*](https://md.research.elamur.ai/free/en/papers/mines-2026-multilingual-target-stance-extraction/)
143. [**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/)
144. [**NegNLI-BR: A Brazilian Portuguese Benchmark for Negation in Natural Language Inference**Matheus Westhelle, Viviane Moreira*2026*](https://md.research.elamur.ai/free/en/papers/westhelle-2026-negnli-br-brazilian-portuguese-benchmark/)
145. [**On the Robustness of Morphosyntactic Transformation with Large Language Models: The Case of Quechua Collao**Pool Pocco, Arturo Oncevay*2026*](https://md.research.elamur.ai/free/en/papers/pocco-2026-robustness-morphosyntactic-transformation-large-language/)
146. [**Proficiency-Controlled Text Simplification in European Portuguese: A Preliminary Study using Prompting Approaches**Eugénio Ribeiro, David Antunes, Nuno Mamede, et al.*2026*](https://md.research.elamur.ai/free/en/papers/ribeiro-2026-proficiency-controlled-text-simplification-european/)
147. [**Quality and Appropriateness of Large Text Datasets for Irish NLP**Abigail Walsh, Mark Andrade, Jane Lauren Adkins, et al.*2026*](https://md.research.elamur.ai/free/en/papers/walsh-2026-quality-appropriateness-large-text-datasets/)
148. [**RadTimeline: Timeline Summarization for Longitudinal Radiological Lung Findings**Sitong Zhou, Meliha Yetisgen, Mari Ostendorf*2026*](https://md.research.elamur.ai/free/en/papers/zhou-2026-radtimeline-timeline-summarization-longitudinal-radiological/)
149. [**RelEx-PT: A Portuguese Sentence-Level Relation Extraction Dataset**Tomás Pinto, Catarina Silva, Hugo Goncalo Oliveira*2026*](https://md.research.elamur.ai/free/en/papers/pinto-2026-relex-pt-portuguese-sentence-level/)
150. [**SalamahBench: Dialect and Category Level Safety Evaluation of Arabic Language Models**Omar Abdelnasser, Fatemah Alharbi, Khaled Khasawneh, et al.*2026*](https://md.research.elamur.ai/free/en/papers/abdelnasser-2026-salamahbench-dialect-category-level-safety/)
151. [**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/)
152. [**STAGEET: Stage-wise Typed Edit Tagging for Grammatical Error Correction with Arabic as a Case Study**Wenjie Lou, Alaa Mamdouh Akef*2026*](https://md.research.elamur.ai/free/en/papers/lou-2026-stageet-stage-wise-typed-edit/)
153. [**Stands to Reason: Investigating the Effect of Reasoning on Idiomaticity Detection**Dylan Phelps, Rodrigo Wilkens, Edward Gow-Smith, et al.*2026*](https://md.research.elamur.ai/free/en/papers/phelps-2026-stands-reason-investigating-effect-reasoning/)
154. [**STRUDEL: Unrolling a Benchmark for Evaluating Vision-Language Models on Structured Diagram Understanding across Domains**Daniel Steinigen, Lucie Flek, Sebastian Houben*2026*](https://md.research.elamur.ai/free/en/papers/steinigen-2026-strudel-unrolling-benchmark-evaluating-vision/)
155. [**The Surge of Anti-Semitism in German Social Media following the October 7 Attacks**Gregor Wiedemann, Daniel Wehrend*2026*](https://md.research.elamur.ai/free/en/papers/wiedemann-2026-surge-anti-semitism-german-social/)
156. [**Translation as Augmentation: Effect of Translated Data on Assessment of Difficulty**Yiheng Wu, Jue Hou, Roman Yangarber*2026*](https://md.research.elamur.ai/free/en/papers/wu-2026-translation-as-augmentation-effect-translated/)
157. [**Tree-Based Interview Topic Guidance for Collecting Target Information under Adaptive Topic continuation/switching**Fuminori Nagasawa, Ekai Hashimoto, Shun Shiramatsu*2026*](https://md.research.elamur.ai/free/en/papers/nagasawa-2026-tree-based-interview-topic-guidance/)
158. [**Uncovering Hidden Violent Tendencies in LLMs: A Demographic Analysis via Behavioral Vignettes**Quintin Myers, Yanjun Gao*2026*](https://md.research.elamur.ai/free/en/papers/myers-2026-uncovering-hidden-violent-tendencies-llms/)
159. [**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/)
160. [**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/)
161. [**Why do Large Language Models Fail in Low-resource Translation? Unraveling the Token Dynamics of Large Language Models for Machine Translation**Shenbin Qian, Yves Scherrer*2026*](https://md.research.elamur.ai/free/en/papers/qian-2026-why-do-large-language-models/)
162. [**MuDRiC: Multi-Dialect Reasoning for Arabic Commonsense Validation**Kareem Elozeiri, Mervat Abassy, Preslav Nakov, et al.*2025*](https://md.research.elamur.ai/free/en/papers/elozeiri-2025-mudric-multi-dialect-reasoning-arabic/)
163. [**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/)

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