---
title: "Who cites Jan Deriu — 154 papers of our library"
description: "154 papers of the Elamur Research library cite the works of Jan Deriu, found in their bibliographies; the most cited first."
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---
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# Who cites Jan Deriu

181 citations of their works from 154 papers of our library (of the 149,439 whose bibliographies we read) · 36 with a page here, the most cited first · [← Jan Deriu](https://md.research.elamur.ai/free/en/authors/jan-deriu/)

1. **[SemEval-2016 Task 4: Sentiment Analysis in Twitter](https://md.research.elamur.ai/free/en/papers/nakov-2016-semeval-2016-task-4-sentiment/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Preslav Nakov, Alan Ritter, Sara Rosenthal, et al.*2016 · 1,083 citations*
2. **[Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm](https://md.research.elamur.ai/free/en/papers/felbo-2017-millions-emoji-occurrences-learn-any/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bjarke Felbo, Alan Mislove, Anders Søgaard, et al.*2017 · 621 citations*
3. **[DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/baziotis-2017-datastories-semeval-2017-task-4/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Christos Baziotis, Nikos Pelekis, Christos Doulkeridis*2017 · 588 citations*
4. **[XLM-T: Multilingual Language Models in Twitter for Sentiment Analysis and Beyond](https://md.research.elamur.ai/free/en/papers/barbieri-2022-xlm-t-multilingual-language-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Francesco Barbieri, Luis Espinosa Anke, Jose Camacho-Collados*2022 · 271 citations*
5. **[Corpus Creation for Sentiment Analysis in Code-Mixed Tamil-English Text](https://md.research.elamur.ai/free/en/papers/chakravarthi-2020-corpus-creation-sentiment-analysis-code/) [Joint Workshop on Spoken Language Technologies for Under-resourced languages (SLTU) and Collaboration and Computing for Under-Resourced Languages (CCURL)](https://md.research.elamur.ai/free/en/venues/sltu/)**Bharathi Raja Chakravarthi, Vigneshwaran Muralidaran, Ruba Priyadharshini, et al.*2020 · 234 citations*
6. **[Language Identification and Morphosyntactic Tagging: The Second VarDial Evaluation Campaign](https://md.research.elamur.ai/free/en/papers/zampieri-2018-language-identification-morphosyntactic-tagging-second/) [Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial)](https://md.research.elamur.ai/free/en/venues/vardial/)**Marcos Zampieri, Shervin Malmasi, Preslav Nakov, et al.*2018 · 170 citations*
7. **[A Sentiment Analysis Dataset for Code-Mixed Malayalam-English](https://md.research.elamur.ai/free/en/papers/chakravarthi-2020-sentiment-analysis-dataset-code-mixed/) [Joint Workshop on Spoken Language Technologies for Under-resourced languages (SLTU) and Collaboration and Computing for Under-Resourced Languages (CCURL)](https://md.research.elamur.ai/free/en/venues/sltu/)**Bharathi Raja Chakravarthi, Navya Jose, Shardul Suryawanshi, et al.*2020 · 158 citations*
8. [**Olmo 3 arXiv:2512.13961**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 130 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/)
9. **[Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Art](https://md.research.elamur.ai/free/en/papers/liu-2025-culturally-aware-adapted-nlp-taxonomy/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Chen Cecilia Liu, Iryna Gurevych, Anna Korhonen*2025 · 90 citations*
10. **[A Characterization Study of Arabic Twitter Data with a Benchmarking for State-of-the-Art Opinion Mining Models](https://md.research.elamur.ai/free/en/papers/baly-2017-characterization-study-arabic-twitter-data/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Ramy Baly, Gilbert Badaro, Georges El-Khoury, et al.*2017 · 67 citations*
11. **[Casablanca: Data and Models for Multidialectal Arabic Speech Recognition](https://md.research.elamur.ai/free/en/papers/talafha-2024-casablanca-data-models-multidialectal-arabic/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bashar Talafha, Karima Kadaoui, Samar Mohamed Magdy, et al.*2024 · 45 citations*
12. [**We Usually Don't Like Going to the Dentist: Using Common Sense to Detect Irony on Twitter**Cynthia Van Hee, Els Lefever, Véronique Hoste*2018 · 39 citations*](https://md.research.elamur.ai/free/en/papers/hee-2018-we-usually-don-t-like/)
13. **[INGEOTEC at SemEval 2017 Task 4: A B4MSA Ensemble based on Genetic Programming for Twitter Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/jimenez-2017-ingeotec-semeval-2017-task-4/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Sabino Miranda-Jiménez, Mario Graff, Eric Sadit Tellez, et al.*2017 · 18 citations*
14. **[Parity-Aware Byte-Pair Encoding: Improving Cross-lingual Fairness in Tokenization](https://md.research.elamur.ai/free/en/papers/foroutan-2026-parity-aware-byte-pair-encoding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Negar Foroutan, Clara Meister, Debjit Paul, et al.*2026 · 12 citations*
15. **[A Multi-Dialectal Dataset for German Dialect ASR and Dialect-to-Standard Speech Translation](https://md.research.elamur.ai/free/en/papers/blaschke-2025-multi-dialectal-dataset-german-dialect/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Verena Blaschke, Miriam Winkler, Constantin Forster, et al.*2025 · 12 citations*
16. **[A Conversational Intelligent Tutoring System for Improving English Proficiency of Non-Native Speakers via Debriefing of Online Meeting Transcriptions](https://md.research.elamur.ai/free/en/papers/ortiz-2024-conversational-intelligent-tutoring-system-improving/) [Workshop on Natural Language Processing for Computer Assisted Language Learning](https://md.research.elamur.ai/free/en/venues/nlp4call/)**Juan Antonio Pérez-Ortiz, Miquel Esplà-Gomis, Víctor M. Sánchez-Cartagena, et al.*2024 · 7 citations*
17. **[Estonian WinoGrande Dataset: Comparative Analysis of LLM Performance on Human and Machine Translation](https://md.research.elamur.ai/free/en/papers/ojastu-2026-estonian-winogrande-dataset-comparative-analysis/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Marii Ojastu, Hele-Andra Kuulmets, Aleksei Dorkin, et al.*2026 · 3 citations*
18. [**A Sovereign, Open-Source Foundation Model for German and English arXiv:2607.09424**Soofi-Team: Benedikt Droste, David Fitzek, Ruben Harle, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/droste-2026-sovereign-open-source-foundation-model/)
19. **[ALBA: A European Portuguese Benchmark for Evaluating Language and Linguistic Dimensions in Generative LLMs](https://md.research.elamur.ai/free/en/papers/vieira-2026-alba-european-portuguese-benchmark-evaluating/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Inês Vieira, Inês Calvo, Iago Paulo, et al.*2026 · 2 citations*
20. **[AMALIA: A Fully Open Large Language Model for European Portuguese](https://md.research.elamur.ai/free/en/papers/simplicio-2026-amalia-fully-open-large-language/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Afonso Simplício, Gonçalo Vinagre, Miguel Moura Ramos, et al.*2026 · 1 citation*
21. [**MÖVE: A Holistic LLM Benchmark for the German Public Sector arXiv:2606.13111**Camilla Dalerci, Thilo Michael, Robin Schaefer, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/dalerci-2026-m-ove-holistic-llm-benchmark/)
22. **[When AI Writes, Whose Voice Remains? Quantifying Cultural Marker Erasure Across World English Varieties in Large Language Models](https://md.research.elamur.ai/free/en/papers/navneet-2026-ai-writes-whose-voice-remains/) [Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA)](https://md.research.elamur.ai/free/en/venues/extended-abstracts-of-the-chi-conference-on-human-factors-in-computing-systems/)**Satyam Kumar Navneet, Joydeep Chandra, Yong Zhang*2026 · 1 citation*
23. **[Are the LLMs Capable of Maintaining at Least the Language Genus?](https://md.research.elamur.ai/free/en/papers/mitrovic-2026-are-llms-capable-maintaining-least/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Sandra Mitrović, David Kletz, Ljiljana Dolamic, et al.*2026*
24. **[Benchmarking NLP-supported Language Sample Analysis for Swiss Children's Speech](https://md.research.elamur.ai/free/en/papers/ryser-2026-benchmarking-nlp-supported-language-sample/) [Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments in cooperation with the MENTAL.ai consortium](https://md.research.elamur.ai/free/en/venues/rapid/)**Anja Ryser, Yingqiang Gao, Sarah Ebling*2026*
25. **[Can Large Language Models Replace Statistical Software?](https://md.research.elamur.ai/free/en/papers/staudt-2026-can-large-language-models-replace/) [Edition of the Swiss Text Analytics Conference](https://md.research.elamur.ai/free/en/venues/swisstext/)**Yves Staudt*2026*
26. **[EIFFEL: a novel benchmark to measure bias of English heavy training on French idiomatic expressions](https://md.research.elamur.ai/free/en/papers/noel-2026-eiffel-novel-benchmark-measure-bias/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Charlotte Noel, Nicholas Asher, Olivier Gouvert, et al.*2026*
27. **[Graph-Augmented LLMs for Swiss MP Ideology Prediction](https://md.research.elamur.ai/free/en/papers/yuan-2026-graph-augmented-llms-swiss-mp/) [Edition of the Swiss Text Analytics Conference](https://md.research.elamur.ai/free/en/venues/swisstext/)**Yifei Yuan, Luis Salamanca, Sophia Schlosser, et al.*2026*
28. **[Is Biomedical Specialization Still Worth It? Insights from Domain-Adaptive Language Modelling with a New French Health Corpus](https://md.research.elamur.ai/free/en/papers/mannion-2026-is-biomedical-specialization-still-worth/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aidan Mannion, Cécile Macaire, Armand Violle, et al.*2026*
29. [**LuxSQA: Ask Me in Luxembourgish with TTS-Augmented Spoken Question Answering arXiv:2607.02763**Nina Hosseini-Kivanani, Marco Matassoni, Alessio Brutti*2026*](https://md.research.elamur.ai/free/en/papers/hosseini-kivanani-2026-luxsqa-ask-me-luxembourgish-tts/)
30. **[Par-ITA: Benchmarking Seq2Seq and LLMs on a Human-Supervised Parallel Corpus for Italian Hyperpartisan Neutralization](https://md.research.elamur.ai/free/en/papers/maggini-2026-par-ita-benchmarking-seq2seq-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michele Joshua Maggini, Søren Fomsgaard, Michele Maestroni, et al.*2026*
31. **[POS Tagging with Generative LLMs for Historical Germanic Low-Resource Languages: An Evaluation Against Fine-Tuned BERT](https://md.research.elamur.ai/free/en/papers/miani-2026-pos-tagging-generative-llms-historical/) [Workshop on Language Technologies for Historical and Ancient Languages @ LREC](https://md.research.elamur.ai/free/en/venues/lt4hala/)**Irene Miani, Gregory Darwin, Sara Stymne*2026*
32. [**Reading the News: Adapting Large Language Models to Swedish Journalism Through Continued Pre-Training arXiv:2608.30609**Lukas Borggren, Jenny Kunz, Marco Kuhlmann*2026*](https://md.research.elamur.ai/free/en/papers/borggren-2026-reading-news-adapting-large-language/)
33. **[Regional Variation in the Performance of ASR Models on Croatian and Serbian](https://md.research.elamur.ai/free/en/papers/samardzic-2026-regional-variation-performance-asr-models/) [Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial)](https://md.research.elamur.ai/free/en/venues/vardial/)**Tanja Samardžić, Peter Rupnik, Nikola Ljubešić*2026*
34. **[Robust Language Identification for Romansh Varieties](https://md.research.elamur.ai/free/en/papers/model-2026-robust-language-identification-romansh-varieties/) [Edition of the Swiss Text Analytics Conference](https://md.research.elamur.ai/free/en/venues/swisstext/)**Charlotte Model, Sina Ahmadi, Jannis Vamvas*2026*
35. [**Subtitle-Aligned Fine-Tuning of Whisper for Swiss German ASR: Benchmark Contamination, Convention Mismatch, and an Honest Baseline at 25.6% WER (13.8% cWER) arXiv:2606.07608**Felix Akeret*2026*](https://md.research.elamur.ai/free/en/papers/akeret-2026-subtitle-aligned-fine-tuning-whisper/)
36. **[Why do Large Language Models Fail in Low-resource Translation? Unraveling the Token Dynamics of Large Language Models for Machine Translation](https://md.research.elamur.ai/free/en/papers/qian-2026-why-do-large-language-models/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Shenbin Qian, Yves Scherrer*2026*

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

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