---
title: "Who cites Rotem Dror — 516 papers of our library"
description: "516 papers of the Elamur Research library cite the works of Rotem Dror, found in their bibliographies; the most cited first."
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---
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# Who cites Rotem Dror

568 citations of their works from 516 papers of our library (of the 149,439 whose bibliographies we read) · 73 with a page here, the most cited first · [← Rotem Dror](https://md.research.elamur.ai/free/en/authors/rotem-dror/)

1. **[Fact or Fiction: Verifying Scientific Claims](https://md.research.elamur.ai/free/en/papers/wadden-2020-fact-or-fiction-verifying-scientific/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**David Wadden, Shanchuan Lin, Kyle Lo, et al.*2020 · 709 citations*
2. **[MixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classification](https://md.research.elamur.ai/free/en/papers/chen-2020-mixtext-linguistically-informed-interpolation-hidden/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaao Chen, Zichao Yang, Diyi Yang*2020 · 417 citations*
3. **[Re-evaluating Evaluation in Text Summarization](https://md.research.elamur.ai/free/en/papers/bhandari-2020-re-evaluating-evaluation-text-summarization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Manik Bhandari, Pranav Narayan Gour, Atabak Ashfaq, et al.*2020 · 259 citations*
4. **[CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary Representations From Characters](https://md.research.elamur.ai/free/en/papers/boukkouri-2020-characterbert-reconciling-elmo-bert-word/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Hicham El Boukkouri, Olivier Ferret, Thomas Lavergne, et al.*2020 · 206 citations*
5. **[Toxicity Detection: Does Context Really Matter?](https://md.research.elamur.ai/free/en/papers/pavlopoulos-2020-toxicity-detection-does-context-really/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**John Pavlopoulos, Jeffrey Sorensen, Lucas Dixon, et al.*2020 · 199 citations*
6. **[Speak, Memory: An Archaeology of Books Known to ChatGPT/GPT-4](https://md.research.elamur.ai/free/en/papers/chang-2023-speak-memory-archaeology-books-known/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kent K. Chang, Mackenzie Cramer, Sandeep Soni, et al.*2023 · 169 citations*
7. **[Results of the WMT21 Metrics Shared Task: Evaluating Metrics with Expert-based Human Evaluations on TED and News Domain](https://md.research.elamur.ai/free/en/papers/freitag-2021-results-wmt21-metrics-shared-task/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Markus Freitag, Ricardo Rei, Nitika Mathur, et al.*2021 · 169 citations*
8. **[Results of WMT23 Metrics Shared Task: Metrics Might Be Guilty but References Are Not Innocent](https://md.research.elamur.ai/free/en/papers/freitag-2023-results-wmt23-metrics-shared-task/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Markus Freitag, Nitika Mathur, Chi-kiu Lo, et al.*2023 · 155 citations*
9. [**ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning arXiv:2212.07919**Olga Golovneva, Moya Chen, Spencer Poff, et al.*2022 · 155 citations*](https://md.research.elamur.ai/free/en/papers/golovneva-2022-roscoe-suite-metrics-scoring-step/)
10. **[Towards Question-Answering as an Automatic Metric for Evaluating the Content Quality of a Summary](https://md.research.elamur.ai/free/en/papers/deutsch-2021-question-answering-as-automatic-metric/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Daniel Deutsch, Tania Bedrax-Weiss, Dan Roth*2021 · 152 citations*
11. [**Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing arXiv:2406.08464**Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.*2024 · 148 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-magpie-alignment-data-synthesis-scratch/)
12. **[Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2024-error-analysis-prompting-enables-human/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qingyu Lu, Baopu Qiu, Liang Ding, et al.*2024 · 136 citations*
13. **[Structure-Aware Abstractive Conversation Summarization via Discourse and Action Graphs](https://md.research.elamur.ai/free/en/papers/chen-2021-structure-aware-abstractive-conversation-summarization/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jiaao Chen, Diyi Yang*2021 · 135 citations*
14. **[Syntax-Guided Controlled Generation of Paraphrases](https://md.research.elamur.ai/free/en/papers/kumar-2020-syntax-guided-controlled-generation-paraphrases/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ashutosh Kumar, Kabir Ahuja, Raghuram Vadapalli, et al.*2020 · 131 citations*
15. **[High Quality Rather than High Model Probability: Minimum Bayes Risk Decoding with Neural Metrics](https://md.research.elamur.ai/free/en/papers/freitag-2022-high-quality-rather-than-high/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Markus Freitag, David Grangier, Qijun Tan, et al.*2022 · 121 citations*
16. **[Findings of the AmericasNLP 2021 Shared Task on Open Machine Translation for Indigenous Languages of the Americas](https://md.research.elamur.ai/free/en/papers/mager-2021-findings-americasnlp-2021-shared-task/) [Workshop on NLP for Indigenous Languages of the Americas (AmericasNLP)](https://md.research.elamur.ai/free/en/venues/americasnlp/)**Manuel Mager, Arturo Oncevay, Abteen Ebrahimi, et al.*2021 · 120 citations*
17. [**Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation arXiv:2212.07981**Yixin Liu, Alexander R. Fabbri, Pengfei Liu, et al.*2022 · 117 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-revisiting-gold-standard-grounding-summarization/)
18. **[A Statistical Analysis of Summarization Evaluation Metrics Using Resampling Methods](https://md.research.elamur.ai/free/en/papers/deutsch-2021-statistical-analysis-summarization-evaluation-metrics/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Daniel Deutsch, Rotem Dror, Dan Roth*2021 · 117 citations*
19. **[LongEval: Guidelines for Human Evaluation of Faithfulness in Long-form Summarization](https://md.research.elamur.ai/free/en/papers/krishna-2023-longeval-guidelines-human-evaluation-faithfulness/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Kalpesh Krishna, Erin Bransom, Bailey Kuehl, et al.*2023 · 114 citations*
20. **[CDLM: Cross-Document Language Modeling](https://md.research.elamur.ai/free/en/papers/caciularu-2021-cdlm-cross-document-language-modeling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Avi Caciularu, Arman Cohan, Iz Beltagy, et al.*2021 · 106 citations*
21. **[LENS: A Learnable Evaluation Metric for Text Simplification](https://md.research.elamur.ai/free/en/papers/maddela-2023-lens-learnable-evaluation-metric-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mounica Maddela, Yao Dou, David Heineman, et al.*2023 · 104 citations*
22. **[SciFact-Open: Towards open-domain scientific claim verification](https://md.research.elamur.ai/free/en/papers/wadden-2022-scifact-open-open-domain-scientific/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**David Wadden, Kyle Lo, Bailey Kuehl, et al.*2022 · 94 citations*
23. **[How to Train Long-Context Language Models (Effectively)](https://md.research.elamur.ai/free/en/papers/gao-2025-how-train-long-context-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Gao, Alexander Wettig, Howard Yen, et al.*2025 · 89 citations*
24. **[Pride and Prejudice: LLM Amplifies Self-Bias in Self-Refinement](https://md.research.elamur.ai/free/en/papers/xu-2024-pride-prejudice-llm-amplifies-self/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenda Xu, Guanglei Zhu, Xuandong Zhao, et al.*2024 · 88 citations*
25. **[Analyzing Dataset Annotation Quality Management in the Wild](https://md.research.elamur.ai/free/en/papers/klie-2024-analyzing-dataset-annotation-quality-management/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Jan-Christoph Klie, Richard Eckart de Castilho, Iryna Gurevych*2024 · 76 citations*
26. [**Self-Preference Bias in LLM-as-a-Judge arXiv:2410.21819**Koki Wataoka, Tsubasa Takahashi, Ryokan Ri*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/wataoka-2024-self-preference-bias-llm-judge/)
27. **[Embarrassingly Easy Document-Level MT Metrics: How to Convert Any Pretrained Metric into a Document-Level Metric](https://md.research.elamur.ai/free/en/papers/vernikos-2022-embarrassingly-easy-document-level-mt/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Giorgos Vernikos, Brian Thompson, Prashant Mathur, et al.*2022 · 68 citations*
28. **[The Alternative Annotator Test for LLM-as-a-Judge: How to Statistically Justify Replacing Human Annotators with LLMs](https://md.research.elamur.ai/free/en/papers/calderon-2025-alternative-annotator-test-llm-as/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nitay Calderon, Roi Reichart, Rotem Dror*2025 · 52 citations*
29. **[Attribute First, then Generate: Locally-attributable Grounded Text Generation](https://md.research.elamur.ai/free/en/papers/slobodkin-2024-attribute-first-then-generate-locally/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aviv Slobodkin, Eran Hirsch, Arie Cattan, et al.*2024 · 48 citations*
30. [**Paraphrasing vs Coreferring: Two Sides of the Same Coin arXiv:2004.14979**Yehudit Meged, Avi Caciularu, Vered Shwartz, et al.*2020 · 47 citations*](https://md.research.elamur.ai/free/en/papers/meged-2020-paraphrasing-vs-coreferring-two-sides/)
31. **[Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning](https://md.research.elamur.ai/free/en/papers/shi-2023-language-models-improve-event-prediction/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoming Shi, Siqiao Xue, Kangrui Wang, et al.*2023 · 44 citations*
32. **[Do Language Models Enjoy Their Own Stories? Prompting Large Language Models for Automatic Story Evaluation](https://md.research.elamur.ai/free/en/papers/chhun-2024-do-language-models-enjoy-their/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Cyril Chhun, Fabian M. Suchanek, Chloé Clavel*2024 · 41 citations*
33. **[Interactively-Propagative Attention Learning for Implicit Discourse Relation Recognition](https://md.research.elamur.ai/free/en/papers/ruan-2020-interactively-propagative-attention-learning-implicit/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Huibin Ruan, Yu Hong, Yang Xu, et al.*2020 · 35 citations*
34. **[Multi-task Active Learning for Pre-trained Transformer-based Models](https://md.research.elamur.ai/free/en/papers/rotman-2022-multi-task-active-learning-pre/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Guy Rotman, Roi Reichart*2022 · 30 citations*
35. [**A Multitask Learning Approach for Diacritic Restoration**Sawsan Alqahtani, Ajay Mishra, Mona Diab*2020 · 28 citations*](https://md.research.elamur.ai/free/en/papers/alqahtani-2020-multitask-learning-approach-diacritic-restoration/)
36. **[Guardians of the Machine Translation Meta-Evaluation: Sentinel Metrics Fall In!](https://md.research.elamur.ai/free/en/papers/perrella-2024-guardians-machine-translation-meta-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Stefano Perrella, Lorenzo Proietti, Alessandro Scirè, et al.*2024 · 24 citations*
37. **[Bridging Argument Quality and Deliberative Quality Annotations with Adapters](https://md.research.elamur.ai/free/en/papers/falk-2023-bridging-argument-quality-deliberative-quality/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Neele Falk, Gabriella Lapesa*2023 · 21 citations*
38. [**Learning Scalar Adjective Intensity from Paraphrases**Anne Cocos, Skyler Wharton, Ellie Pavlick, et al.*2018 · 21 citations*](https://md.research.elamur.ai/free/en/papers/cocos-2018-learning-scalar-adjective-intensity-paraphrases/)
39. **[SemEval-2026 Task 10: PsyCoMark – Psycholinguistic Conspiracy Marker Extraction and Detection](https://md.research.elamur.ai/free/en/papers/samory-2026-semeval-2026-task-10-psycomark/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Mattia Samory, Felix Soldner, Veronika Batzdorfer*2026 · 20 citations*
40. **[The AI Gap: How Socioeconomic Status Affects Language Technology Interactions](https://md.research.elamur.ai/free/en/papers/bassignana-2025-ai-gap-how-socioeconomic-status/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Elisa Bassignana, Amanda Cercas Curry, Dirk Hovy*2025 · 20 citations*
41. **[How to Select Datapoints for Efficient Human Evaluation of NLG Models?](https://md.research.elamur.ai/free/en/papers/zouhar-2025-how-select-datapoints-efficient-human/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Vilém Zouhar, Peng Cui, Mrinmaya Sachan*2025 · 17 citations*
42. **[Bridging Cultural Nuances in Dialogue Agents through Cultural Value Surveys](https://md.research.elamur.ai/free/en/papers/cao-2024-bridging-cultural-nuances-dialogue-agents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yong Cao, Min Chen, Daniel Hershcovich*2024 · 16 citations*
43. **[JuStRank: Benchmarking LLM Judges for System Ranking](https://md.research.elamur.ai/free/en/papers/gera-2025-justrank-benchmarking-llm-judges-system/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ariel Gera, Odellia Boni, Yotam Perlitz, et al.*2025 · 15 citations*
44. **[URIEL+: Enhancing Linguistic Inclusion and Usability in a Typological and Multilingual Knowledge Base](https://md.research.elamur.ai/free/en/papers/khan-2025-uriel-enhancing-linguistic-inclusion-usability/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Aditya Khan, Mason Shipton, David Anugraha, et al.*2025 · 15 citations*
45. **[Enhancing Automated Interpretability with Output-Centric Feature Descriptions](https://md.research.elamur.ai/free/en/papers/arieh-2025-enhancing-automated-interpretability-output-centric/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yoav Gur-Arieh, Roy Mayan, Chen Agassy, et al.*2025 · 13 citations*
46. [**CamelParser2.0: A State-of-the-Art Dependency Parser for Arabic**Ahmed Elshabrawy, Muhammed AbuOdeh, Go Inoue, et al.*2023 · 13 citations*](https://md.research.elamur.ai/free/en/papers/elshabrawy-2023-camelparser2-0-state-art-dependency/)
47. **[Whose Boat Does it Float? Improving Personalization in Preference Tuning via Inferred User Personas](https://md.research.elamur.ai/free/en/papers/balepur-2025-whose-boat-does-it-float/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nishant Balepur, Vishakh Padmakumar, Fumeng Yang, et al.*2025 · 12 citations*
48. **[A Survey of Inductive Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2026-survey-inductive-reasoning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kedi Chen, Dezhao Ruan, Yuhao Dan, et al.*2026 · 10 citations*
49. [**Dependency Parsing Evaluation for Low-resource Spontaneous Speech**Zoey Liu, Emily Prud'hommeaux*2021 · 6 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-dependency-parsing-evaluation-low-resource/)
50. **[Increasing Robustness for Cross-domain Dialogue Act Classification on Social Media Data](https://md.research.elamur.ai/free/en/papers/vielsted-2022-increasing-robustness-cross-domain-dialogue/) [Workshop on Noisy User-generated Text](https://md.research.elamur.ai/free/en/venues/wnut/)**Marcus Vielsted, Nikolaj Wallenius, Rob van der Goot*2022 · 3 citations*
51. **[MALicious INTent Dataset and Inoculating LLMs for Enhanced Disinformation Detection](https://md.research.elamur.ai/free/en/papers/modzelewski-2026-malicious-intent-dataset-inoculating-llms/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Arkadiusz Modzelewski, Witold Sosnowski, Eleni Papadopulos, et al.*2026 · 2 citations*
52. **[Remedy-R: Generative Reasoning for Machine Translation Evaluation without Error Annotations](https://md.research.elamur.ai/free/en/papers/tan-2026-remedy-r-generative-reasoning-machine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shaomu Tan, Ryosuke Mitani, Ritvik Choudhary, et al.*2026 · 2 citations*
53. **[Improving the OOD Performance of Closed-Source LLMs on NLI Through Strategic Data Selection](https://md.research.elamur.ai/free/en/papers/stacey-2026-improving-ood-performance-closed-source/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Joe Stacey, Lisa Alazraki, Aran Ubhi, et al.*2026 · 1 citation*
54. **[PEAR: Pairwise Evaluation for Automatic Relative Scoring in Machine Translation](https://md.research.elamur.ai/free/en/papers/proietti-2026-pear-pairwise-evaluation-automatic-relative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lorenzo Proietti, Roman Grundkiewicz, Matt Post*2026 · 1 citation*
55. **[SycoBench-600: Measuring Sycophancy and Correction Selectivity in LLM Assistants](https://md.research.elamur.ai/free/en/papers/sinha-2026-sycobench-600-measuring-sycophancy-correction/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Debu Sinha*2026 · 1 citation*
56. **[When LLMs Annotate: Reliability Challenges in Low-Resource NLI](https://md.research.elamur.ai/free/en/papers/panahi-2026-when-llms-annotate-reliability-challenges/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Solmaz Panahi, John Kelleher, Vasudevan Nedumpozhimana*2026 · 1 citation*
57. **[Attribute-Controlled Translation with Preference Optimization](https://md.research.elamur.ai/free/en/papers/unanue-2026-attribute-controlled-translation-preference-optimization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Inigo Jauregi Unanue, Najmeh Sadoughi, Vimal Bhat, et al.*2026*
58. [**BenGER: Benchmarking LLM Systems on Subsumption-Based Legal Reasoning in German Law arXiv:2605.28183**Sebastian Nagl, Ann-Kristin Mayrhofer, Martin Heidebach, et al.*2026*](https://md.research.elamur.ai/free/en/papers/nagl-2026-benger-benchmarking-llm-systems-subsumption/)
59. **[Can AI-Generated Persuasion Be Detected? Persuaficial Benchmark and AI vs. Human Linguistic Differences](https://md.research.elamur.ai/free/en/papers/modzelewski-2026-can-ai-generated-persuasion-be/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Arkadiusz Modzelewski, Paweł Golik, Anna Kołos, et al.*2026*
60. **[Diagnosing Translated Benchmarks: An Automated Quality Assurance Study of the EU20 Benchmark Suite](https://md.research.elamur.ai/free/en/papers/thellmann-2026-diagnosing-translated-benchmarks-automated-quality/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Klaudia Thellmann, Bernhard Stadler, Michael Färber*2026*
61. [**Don't ‘Well, Actually' Me Unless You Know What You're Talking About: Weak Presupposition Verification Degrades General QA Performance arXiv:2608.06539**Shenran Wang, Vered Shwartz, Hila Gonen*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-don-t-well-actually-me/)
62. **[From Bones to Rocks: A Systematic Evaluation of Specialized Definition Generation for Portuguese](https://md.research.elamur.ai/free/en/papers/nunes-2026-bones-rocks-systematic-evaluation-specialized/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Rafael Oleques Nunes, Dennis Giovani Balreira, Joel Luís Carbonera*2026*
63. [**How Does "English (US)" Become the Default? Triangulating Structural Bias Towards American English Across the LLM Pipeline arXiv:2604.04204**Mir Tafseer Nayeem, Davood Rafiei*2026*](https://md.research.elamur.ai/free/en/papers/nayeem-2026-english-us-become-default-triangulating/)
64. **[How Much Would a Clinician Edit This Draft? Evaluating LLM Alignment for Patient Message Response Drafting](https://md.research.elamur.ai/free/en/papers/seegmiller-2026-how-much-would-clinician-edit/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Parker Seegmiller, Joseph Gatto, Sarah E. Greer, et al.*2026*
65. **[Human vs LLM in Conversational Repair Annotation: A New Resource and Comparative Study](https://md.research.elamur.ai/free/en/papers/ngo-2026-human-vs-llm-conversational-repair/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Anh Ngo, Nicolas Rollet, Catherine Pelachaud, et al.*2026*
66. **[Medical Summarization in Practice: Design, Deployment, and Analysis of a Clinical Summarization System for a German Hospital](https://md.research.elamur.ai/free/en/papers/rauf-2026-medical-summarization-practice-design-deployment/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Moiz Rauf, Sean Papay*2026*
67. **[M²PO: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation](https://md.research.elamur.ai/free/en/papers/wang-2026-m-2-po-multi-perspective/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Wang, Linlong Xu, Heng Liu, et al.*2026*
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71. [**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/)
72. [**LLM Analysis of 150+ years of German Parliamentary Debates on Migration Reveals Shift from Post-War Solidarity to Anti-Solidarity in the Last Decade arXiv:2509.07274**Aida Kostikova, Ole Putz, Steffen Eger, et al.*2025*](https://md.research.elamur.ai/free/en/papers/kostikova-2025-llm-analysis-150-years-german/)
73. [**The Truth, The Whole Truth, and Nothing but the Truth: A New Benchmark Dataset for Hebrew Text Credibility Assessment**Ben Hagag, Reut Tsarfaty*2023*](https://md.research.elamur.ai/free/en/papers/hagag-2023-truth-whole-truth-nothing-but/)

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