---
title: "Who cites Dustin Schwenk — page 3 — 1,364 citing papers"
description: "1,364 papers of the Elamur Research library cite the works of Dustin Schwenk, found in their bibliographies · page 3 of 4 · 201–300; the most…"
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---
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# Who cites Dustin Schwenk

1,670 citations of their works from 1,364 papers of our library (of the 149,439 whose bibliographies we read) · 332 with a page here, the most cited first · page 3 of 4 · 201–300 · [← Dustin Schwenk](https://md.research.elamur.ai/free/en/authors/dustin-schwenk/)

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201. **[Mitigating Catastrophic Forgetting in Target Language Adaptation of LLMs via Source-Shielded Updates](https://md.research.elamur.ai/free/en/papers/yamaguchi-2026-mitigating-catastrophic-forgetting-target-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Atsuki Yamaguchi, Terufumi Morishita, Aline Villavicencio, et al.*2026 · 3 citations*
202. **[Task Matters: Knowledge Requirements Shape LLM Responses to Context–Memory Conflict](https://md.research.elamur.ai/free/en/papers/sun-2026-task-matters-knowledge-requirements-shape/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaiser Sun, Fan Bai, Mark Dredze*2026 · 3 citations*
203. **[Adapting Psycholinguistic Research for LLMs: Gender-inclusive Language in a Coreference Context](https://md.research.elamur.ai/free/en/papers/bartl-2025-adapting-psycholinguistic-research-llms-gender/) [Workshop on Gender Bias in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/gebnlp/)**Marion Bartl, Thomas Brendan Murphy, Susan Leavy*2025 · 3 citations*
204. [**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/)
205. **[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*
206. [**Dicta-LM 3.0: Advancing The Frontier of Hebrew Sovereign LLMs**Shaltiel Shmidman, Avi Shmidman, Amir DN Cohen, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2026-dicta-lm-3-0-advancing/)
207. **[Do Images Speak Louder than Words? Investigating the Effect of Textual Misinformation in VLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-do-images-speak-louder-than/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Chi Zhang, Wenxuan Ding, Jiale Liu, et al.*2026 · 2 citations*
208. **[HTMuon: Improving Muon via Heavy-Tailed Spectral Correction](https://md.research.elamur.ai/free/en/papers/pang-2026-htmuon-improving-muon-heavy-tailed/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tianyu Pang, Yujie Fang, Zihang Liu, et al.*2026 · 2 citations*
209. **[Improving Romanian LLM Pretraining Data using Diversity and Quality Filtering](https://md.research.elamur.ai/free/en/papers/negoita-2026-improving-romanian-llm-pretraining-data/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Vlad-Andrei Negoiță, Mihai Masala, Traian Rebedea*2026 · 2 citations*
210. **[Kenji-Endo: a BabyLM @EVALITA](https://md.research.elamur.ai/free/en/papers/scozzaro-2026-kenji-endo-babylm-evalita/) [Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop](https://md.research.elamur.ai/free/en/venues/evalita/)**Calogero Jerik Scozzaro, Matteo Rinaldi, Gianluca Mittone, et al.*2026 · 2 citations*
211. **[Logit Arithmetic Elicits Long Reasoning Capabilities Without Training](https://md.research.elamur.ai/free/en/papers/zhang-2026-logit-arithmetic-elicits-long-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yunxiang Zhang, Muhammad Khalifa, Lechen Zhang, et al.*2026 · 2 citations*
212. **[PHEB: An European Portuguese High School-Level LLM Benchmark](https://md.research.elamur.ai/free/en/papers/tavares-2026-pheb-european-portuguese-high-school/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Diogo C. Tavares, Rafael Ferreira, Afonso Simplício, et al.*2026 · 2 citations*
213. **[QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/min-2026-quco-rag-quantifying-uncertainty-pre/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dehai Min, Kailin Zhang, Tongtong Wu, et al.*2026 · 2 citations*
214. **[RefusalBench: Generative Evaluation of Selective Refusal in Grounded Language Models](https://md.research.elamur.ai/free/en/papers/muhamed-2026-refusalbench-generative-evaluation-selective-refusal/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Aashiq Muhamed, Leonardo F. R. Ribeiro, Markus Dreyer, et al.*2026 · 2 citations*
215. **[TechING: Towards Real World Technical Image Understanding via VLMs](https://md.research.elamur.ai/free/en/papers/nadeem-2026-teching-real-world-technical-image/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tafazzul Nadeem, Bhavik Shangari, Manish Rai, et al.*2026 · 2 citations*
216. **[The olmOCR Project: Building Fully Open OCR using VLMs](https://md.research.elamur.ai/free/en/papers/poznanski-2026-olmocr-project-building-fully-open/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jake Poznanski, Kyle Lo, Luca Soldaini*2026 · 2 citations*
217. **[Automatic Extraction of Clausal Embedding Based on Large-Scale English Text Data](https://md.research.elamur.ai/free/en/papers/carslaw-2025-automatic-extraction-clausal-embedding-based/) [Society for Computation in Linguistics (SCiL)](https://md.research.elamur.ai/free/en/venues/scil/)**Iona Carslaw, Sivan Milton, Nicolas Navarre, et al.*2025 · 2 citations*
218. [**The German Commons - 154 Billion Tokens of Openly Licensed Text for German Language Models arXiv:2510.13996**Lukas Gienapp, Christopher Schroder, Stefan Schweter, et al.*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/gienapp-2025-german-commons-154-billion-tokens/)
219. [**Hypothesis-only Biases in Large Language Model-Elicited Natural Language Inference arXiv:2410.08996**Grace Proebsting, Adam Poliak*2024 · 2 citations*](https://md.research.elamur.ai/free/en/papers/proebsting-2024-hypothesis-only-biases-large-language/)
220. **[A Comprehensive Evaluation of Chain-of-Thought Faithfulness in Persian Classification Tasks](https://md.research.elamur.ai/free/en/papers/yazdani-2026-comprehensive-evaluation-chain-thought-faithfulness/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Shakib Yazdani, Cristina España-Bonet, Eleftherios Avramidis, et al.*2026 · 1 citation*
221. **[Addressing the Ecological Fallacy in Larger LMs with Human Context](https://md.research.elamur.ai/free/en/papers/soni-2026-addressing-ecological-fallacy-larger-lms/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Nikita Soni, Dhruv Vijay Kunjadiya, Pratham Piyush Shah, et al.*2026 · 1 citation*
222. **[Aligned Probing: Relating Toxic Behavior and Model Internals](https://md.research.elamur.ai/free/en/papers/waldis-2026-aligned-probing-relating-toxic-behavior/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Andreas Waldis, Vagrant Gautam, Anne Lauscher, et al.*2026 · 1 citation*
223. **[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*
224. **[Among Us: Measuring and Mitigating Malicious Contributions in Model Collaboration Systems](https://md.research.elamur.ai/free/en/papers/yang-2026-among-us-measuring-mitigating-malicious/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyuan Yang, Wenxuan Ding, Shangbin Feng, et al.*2026 · 1 citation*
225. **[BSC's Submission to the Instruction Following Track of IWSLT 2026](https://md.research.elamur.ai/free/en/papers/pareras-2026-bsc-s-submission-instruction-following/) [International Conference on Spoken Language Translation (IWSLT)](https://md.research.elamur.ai/free/en/venues/iwslt/)**Oriol Pareras, Joan Llado, Pol Buitrago, et al.*2026 · 1 citation*
226. **[CoGR-MoE: Concept-Guided Expert Routing with Consistent Selection and Flexible Reasoning for Visual Question Answering](https://md.research.elamur.ai/free/en/papers/zeng-2026-cogr-moe-concept-guided-expert/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiyin Zeng, Yi Lu, Hao Wang*2026 · 1 citation*
227. **[DART: Leveraging Multi-Agent Disagreement for Tool Recruitment in Multimodal Reasoning](https://md.research.elamur.ai/free/en/papers/sivakumaran-2026-dart-leveraging-multi-agent-disagreement/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Nithin Sivakumaran, Justin Chen, David Wan, et al.*2026 · 1 citation*
228. **[Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training](https://md.research.elamur.ai/free/en/papers/yang-2026-data-mixing-agent-learning-re/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kailai Yang, Xiao Liu, Lei Ji, et al.*2026 · 1 citation*
229. **[Evaluating Robustness of Large Language Models Against Multilingual Typographical Errors](https://md.research.elamur.ai/free/en/papers/zhao-2026-evaluating-robustness-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Raoyuan Zhao, Yihong Liu, Lena Altinger, et al.*2026 · 1 citation*
230. **[From Interpretability to Performance: Optimizing Retrieval Heads for Long-Context Language Models](https://md.research.elamur.ai/free/en/papers/ma-2026-interpretability-performance-optimizing-retrieval-heads/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Youmi Ma, Naoaki Okazaki*2026 · 1 citation*
231. **[Ground Then Rank: Revisiting Knowledge-Based VQA with Training-Free Entity Identification](https://md.research.elamur.ai/free/en/papers/ma-2026-ground-then-rank-revisiting-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qian Ma, Qiong Wu, Zhengyi Zhou, et al.*2026 · 1 citation*
232. [**KletterMix: Climbing Toward High-Quality German Pretraining Data - The Full Report arXiv:2606.03773**Maurice Kraus, Ruben Harle, Sebastian Sztwiertnia, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/kraus-2026-klettermix-climbing-toward-high-quality/)
233. **[Language Models Learn Constructional Semantics, Not To Mention Syntax: Investigating LM Understanding of Paired-Focus Constructions](https://md.research.elamur.ai/free/en/papers/scivetti-2026-language-models-learn-constructional-semantics/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Wesley Scivetti, Ethan Gotlieb Wilcox, Nathan Schneider, et al.*2026 · 1 citation*
234. **[NeoAraBERT: A Modern Foundation Model for Arabic Embeddings with Diacritics-Aware Tokenization and POS-Targeted Masking](https://md.research.elamur.ai/free/en/papers/chakra-2026-neoarabert-modern-foundation-model-arabic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chadi Abou Chakra, Hadi Khaled Hamoud, Osama Rakan Al Mraikhat, et al.*2026 · 1 citation*
235. **[OLA: Output Language Alignment in Code-Switched LLM Interactions](https://md.research.elamur.ai/free/en/papers/oh-2026-ola-output-language-alignment-code/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Juhyun Oh, Haneul Yoo, Faiz Ghifari Haznitrama, et al.*2026 · 1 citation*
236. **[Personal Information Parroting in Language Models](https://md.research.elamur.ai/free/en/papers/subramani-2026-personal-information-parroting-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nishant Subramani, Kshitish Ghate, Mona T. Diab*2026 · 1 citation*
237. **[Prior Beliefs Prejudice LLM-as-Judge: Evidence from Persuasion Evaluation](https://md.research.elamur.ai/free/en/papers/zahraei-2026-prior-beliefs-prejudice-llm-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pardis Sadat Zahraei, Xiaoning Wang, Nimet Beyza Bozdag, et al.*2026 · 1 citation*
238. **[Ready to Translate, Not to Represent? Bias and Performance Gaps in Multilingual LLMs Across Language Families and Domains](https://md.research.elamur.ai/free/en/papers/sayeedi-2026-ready-translate-not-represent-bias/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md. Faiyaz Abdullah Sayeedi, Subhey Sadi Rahman, Md. Mahbub Alam, et al.*2026 · 1 citation*
239. **[Reasoning Up the Instruction Ladder for Controllable Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-reasoning-up-instruction-ladder-controllable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zishuo Zheng, Vidhisha Balachandran, Chan Young Park, et al.*2026 · 1 citation*
240. **[Start Making Sense(s): A Developmental Probe of Attention Specialization Using Lexical Ambiguity](https://md.research.elamur.ai/free/en/papers/riviere-2026-start-making-sense-s-developmental/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Pamela D. Rivière, Sean Trott*2026 · 1 citation*
241. **[Test of Time: Rethinking Temporal Signal of Benchmark Contamination](https://md.research.elamur.ai/free/en/papers/zhang-2026-test-time-rethinking-temporal-signal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Terry Jingchen Zhang, Gopal Dev, Ning Wang, et al.*2026 · 1 citation*
242. **[Vocab Diet: Reshaping the Vocabulary of LLMs via Vector Arithmetic](https://md.research.elamur.ai/free/en/papers/reif-2026-vocab-diet-reshaping-vocabulary-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuval Reif, Guy Kaplan, Roy Schwartz*2026 · 1 citation*
243. **[Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models](https://md.research.elamur.ai/free/en/papers/mammen-2026-who-endorsed-it-measuring-authority/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Priyanka Mary Mammen, Emil Joswin, Shankar Venkitachalam*2026 · 1 citation*
244. **[Whose Facts Win? LLM Source Preferences under Knowledge Conflicts](https://md.research.elamur.ai/free/en/papers/schuster-2026-whose-facts-win-llm-source/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jakob Schuster, Vagrant Gautam, Katja Markert*2026 · 1 citation*
245. **[WikiSeeker: Rethinking the Role of Vision-Language Models in Knowledge-Based Visual Question Answering](https://md.research.elamur.ai/free/en/papers/zhu-2026-wikiseeker-rethinking-role-vision-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yingjian Zhu, Xinming Wang, Kun Ding, et al.*2026 · 1 citation*
246. **[ArabicWeb-Edu: Educational Quality Data for Arabic LLM Training](https://md.research.elamur.ai/free/en/papers/hawasly-2025-arabicweb-edu-educational-quality-data/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Majd Hawasly, Tasnim Mohiuddin, Hamdy Mubarak, et al.*2025 · 1 citation*
247. **[Biases in Large Language Model-Elicited Text: A Case Study in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/proebsting-2025-biases-large-language-model-elicited/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Grace Proebsting, Adam Poliak*2025 · 1 citation*
248. [**A Survey on Parameter-efficient Fine-tuning of Large Models: Techniques, Trends, and Challenges (大模型参数高效微调方法综述: 技术、趋势与挑战) Acta Automatica Sinica (自动化学报)**Anda Tang (唐岸达), Zhouchen Lin (林宙辰)*2026*](https://md.research.elamur.ai/free/en/papers/tang-2026-parameter-efficient-fine/)
249. **[AfriqueLLM: How Data Mixing and Model Architecture Impact Continued Pre-training for African Languages](https://md.research.elamur.ai/free/en/papers/yu-2026-afriquellm-how-data-mixing-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Yu, Tianyi Xu, Michael A. Hedderich, et al.*2026*
250. **[AICA-Bench: Holistically Examining the Capabilities of VLMs in Affective Image Content Analysis](https://md.research.elamur.ai/free/en/papers/she-2026-aica-bench-holistically-examining-capabilities/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dong She, Xianrong Yao, Liqun Chen, et al.*2026*
251. **[ANCHOR: LLM-driven Subject Conditioning for Text-to-Image Synthesis](https://md.research.elamur.ai/free/en/papers/ramakrishnan-2026-anchor-llm-driven-subject-conditioning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Aashish Anantha Ramakrishnan, Sharon X Huang, Dongwon Lee*2026*
252. **[Annotation-Efficient Vision-Language Model Adaptation to the Polish Language Using the LLaVA Framework](https://md.research.elamur.ai/free/en/papers/statkiewicz-2026-annotation-efficient-vision-language-model/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Grzegorz Statkiewicz, Alicja Dobrzeniecka, Karolina Seweryn, et al.*2026*
253. **[AYN: A Tiny Yet Competitive Indian Legal Language Model Pretrained from Scratch](https://md.research.elamur.ai/free/en/papers/niyogi-2026-ayn-tiny-yet-competitive-indian/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mitodru Niyogi, Eric Gaussier, Arnab Bhattacharya*2026*
254. **[Benchmarking Deflection and Hallucination in Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/moratelli-2026-benchmarking-deflection-hallucination-large-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nicholas Moratelli, Christopher Davis, Leonardo F. R. Ribeiro, et al.*2026*
255. **[Beyond Ranking: Fine-Grained Diagnostics and Self-Improvement for MLLMs](https://md.research.elamur.ai/free/en/papers/xu-2026-beyond-ranking-fine-grained-diagnostics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingze Xu, Zijing Zhao, Qiming Peng, et al.*2026*
256. **[Beyond Static Synthetic Noise: Assessing the Robustness of Large Language Models to Natural Context Variation in the Real World](https://md.research.elamur.ai/free/en/papers/wu-2026-beyond-static-synthetic-noise-assessing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yulong Wu, Viktor Schlegel, Riza Batista-Navarro*2026*
257. **[Beyond the Panorama: Training-Free Hierarchical Perception-Reasoning for Fine-Grained Vision in MLLMs](https://md.research.elamur.ai/free/en/papers/yi-2026-beyond-panorama-training-free-hierarchical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyang Yi, Jing Chen, Li Peng, et al.*2026*
258. **[Biomed-Enriched: Data-Efficient Biomedical Pretraining via Paragraph-Level Annotation](https://md.research.elamur.ai/free/en/papers/touchent-2026-biomed-enriched-data-efficient-biomedical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rian Touchent, Nathan Godey, Éric Villemonte de la Clergerie*2026*
259. **[Boosting Self-Consistency with Ranking](https://md.research.elamur.ai/free/en/papers/marina-2026-boosting-self-consistency-ranking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Maria Marina, Daniil Moskovskiy, Sergey Pletenev, et al.*2026*
260. **[Breaking the Benchmark: Revealing LLM Bias via Minimal Contextual Augmentation](https://md.research.elamur.ai/free/en/papers/miandoab-2026-breaking-benchmark-revealing-llm-bias/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kaveh Eskandari Miandoab, Mahammed Kamruzzaman, Arshia Gharooni, et al.*2026*
261. **[Can LLMs Reason Like Doctors? Exploring the Limits of Large Language Models in Complex Medical Reasoning](https://md.research.elamur.ai/free/en/papers/merenda-2026-can-llms-reason-like-doctors/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Flavio Merenda, Jose Manuel Gomez-Perez, German Rigau*2026*
262. **[Chart-MRAG: Benchmarking Multimodal Retrieval Augmented Generation on Chart-based Documents](https://md.research.elamur.ai/free/en/papers/ymyang-2026-chart-mrag-benchmarking-multimodal-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ymyang, Jiang Zhong, Li Jin, et al.*2026*
263. **[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*
264. **[Continuous Interpretive Steering for Scalar Diversity](https://md.research.elamur.ai/free/en/papers/cho-2026-continuous-interpretive-steering-scalar-diversity/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ye-eun Cho*2026*
265. **[Curriculum Learning based Hierarchical Scoring and Analysis Framework for Question Answering Task Evaluation](https://md.research.elamur.ai/free/en/papers/wu-2026-curriculum-learning-based-hierarchical-scoring/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiong Wu, Tan Yue, Jianxin Liang, et al.*2026*
266. **[CxMP: A Linguistic Minimal-Pair Benchmark for Evaluating Constructional Understanding in Language Models](https://md.research.elamur.ai/free/en/papers/oba-2026-cxmp-linguistic-minimal-pair-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Miyu Oba, Saku Sugawara*2026*
267. **[Datasets for Scientific Literature Understanding: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2026-datasets-scientific-literature-understanding-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuanzhe Zhang, Xun Zhao, Maodi Hu, et al.*2026*
268. **[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*
269. **[DICA: Dual-Indicator Guided Contrastive Alignment in Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/yang-2026-dica-dual-indicator-guided-contrastive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Yang, Jin Wang, Xuejie Zhang*2026*
270. **[Do Language Models Think Consistently? A Study of Value Preferences Across Varying Response Lengths](https://md.research.elamur.ai/free/en/papers/nair-2026-do-language-models-think-consistently/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Inderjeet Jayakumar Nair, Lu Wang*2026*
271. [**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/)
272. **[Efficient Visual Grounding in VQA via Question-Guided Sparse Attention](https://md.research.elamur.ai/free/en/papers/yadla-2026-efficient-visual-grounding-vqa-question/) [Workshop on Advances in Language and Vision Research (ALVR)](https://md.research.elamur.ai/free/en/venues/alvr/)**Prasanth Yadla*2026*
273. **[EfficientLLM: Unified Pruning-Aware Pretraining for Auto-Designed Compact Language Models](https://md.research.elamur.ai/free/en/papers/xing-2026-efficientllm-unified-pruning-aware-pretraining/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xingrun Xing, Zheng Liu, Shitao Xiao, et al.*2026*
274. **[Embracing Anisotropy: Turning Massive Activations into Interpretable Control Knobs for Large Language Models](https://md.research.elamur.ai/free/en/papers/roh-2026-embracing-anisotropy-turning-massive-activations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Youngji Roh, Hyunjin Cho, Jaehyung Kim*2026*
275. **[Exploring Fine-Tuning for In-Context Retrieval and Efficient KV-Caching in Long-Context Language Models](https://md.research.elamur.ai/free/en/papers/molfese-2026-exploring-fine-tuning-context-retrieval/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Francesco Maria Molfese, Momchil Hardalov, Rexhina Blloshmi, et al.*2026*
276. **[Faithfulness vs. Safety: Evaluating LLM Behavior Under Counterfactual Medical Evidence](https://md.research.elamur.ai/free/en/papers/mo-2026-faithfulness-vs-safety-evaluating-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaijie Mo, Siddhartha Venkatayogi, Chantal Shaib, et al.*2026*
277. **[Far Out: Evaluating Language Models on Slang in Australian and Indian English](https://md.research.elamur.ai/free/en/papers/dilsiz-2026-far-out-evaluating-language-models/) [Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial)](https://md.research.elamur.ai/free/en/venues/vardial/)**Deniz Kaya Dilsiz, Dipankar Srirag, Aditya Joshi*2026*
278. **[GKnow: Measuring the Entanglement of Gender Bias and Factual Gender](https://md.research.elamur.ai/free/en/papers/veloso-2026-gknow-measuring-entanglement-gender-bias/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Leonor Veloso, Hinrich Schuetze*2026*
279. **[GPT-NL Public Corpus: A Permissively Licensed, Dutch-First Dataset for LLM Pre-training](https://md.research.elamur.ai/free/en/papers/oort-2026-gpt-nl-public-corpus-permissively/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Jesse J. Van Oort, Frank Brinkkemper, Erik de Graaf, et al.*2026*
280. **[Harnessing the Latent Space: From Steering Vectors to Model Calibrators for Control and Trust](https://md.research.elamur.ai/free/en/papers/subramani-2026-harnessing-latent-space-steering-vectors/) [Big Picture v2: Crafting a Research Narrative](https://md.research.elamur.ai/free/en/venues/bigpicture/)**Nishant Subramani*2026*
281. **[Heterogeneity in Formal Linguistic Competence of Language Models: Is Data the Real Bottleneck?](https://md.research.elamur.ai/free/en/papers/renduchintala-2026-heterogeneity-formal-linguistic-competence-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**H S V N S Kowndinya Renduchintala, Sumit Bhatia*2026*
282. **[How Can Synthetic Data Improve Multilingual Language Model Pretraining? A Data Quality Perspective](https://md.research.elamur.ai/free/en/papers/zhu-2026-how-can-synthetic-data-improve/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tongyao Zhu, Qian Liu, Chang Ma, et al.*2026*
283. [**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/)
284. **[How Far Can Bias Go? Tracing Bias from Pre-Training Data to Alignment](https://md.research.elamur.ai/free/en/papers/thaler-2026-how-far-can-bias-go/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Marion Thaler, Abdullatif Köksal, Alina Leidinger, et al.*2026*
285. **[Illusions of Confidence? Diagnosing LLM Truthfulness via Neighborhood Consistency](https://md.research.elamur.ai/free/en/papers/xu-2026-illusions-confidence-diagnosing-llm-truthfulness/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoming Xu, Ningyuan Zhao, Yunzhi Yao, et al.*2026*
286. **[Improving Chain-of-Thought for Logical Reasoning via Attention-Aware Intervention](https://md.research.elamur.ai/free/en/papers/nguyen-2026-improving-chain-thought-logical-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Phuong Minh Nguyen, Dang Huu-Tien, Naoya Inoue*2026*
287. **[Infinite Babble: Inflating 3D Vision-Language Model Inference Overhead via Adversarial Geometric Perturbation](https://md.research.elamur.ai/free/en/papers/sun-2026-infinite-babble-inflating-3d-vision/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shuoyang Sun, Jiaxin Hong, Yv Zhang, et al.*2026*
288. **[L2Dir: Integrating L2-Norm and Directional Alignment for Unsupervised Contrastive Representation Learning in Multimodal Retrieval](https://md.research.elamur.ai/free/en/papers/zong-2026-l2dir-integrating-l-2-norm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Zong, Rui Dai, Hongzhu Yi, et al.*2026*
289. **[Language Models Learn Universal Representations of Numbers and Here's Why You Should Care](https://md.research.elamur.ai/free/en/papers/stefanik-2026-language-models-learn-universal-representations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michal Štefánik, Timothee Mickus, Marek Kadlčík, et al.*2026*
290. **[Large-Scale Diverse Synthesis for Mid-Training](https://md.research.elamur.ai/free/en/papers/zhang-2026-large-scale-diverse-synthesis-mid/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuemiao Zhang, Chengying Tu, Can Ren, et al.*2026*
291. **[Learning from Evolving Training Dynamics: An Entropy-Maximizing Data Curation Strategy for LLM Supervised Post-Training](https://md.research.elamur.ai/free/en/papers/zhang-2026-learning-evolving-training-dynamics-entropy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengxiang Zhang, Lingyuan Liu*2026*
292. **[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*
293. **[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*
294. [**MameLoshnLM: Yiddish Language Model and Evaluation Benchmark arXiv:2608.05850 · Proceedings of the Third Conference on Language Modeling (COLM 2026), 2026**Uri Katz, Omer Goldman, Tomasz Limisiewicz, et al.*2026*](https://md.research.elamur.ai/free/en/papers/katz-2026-mameloshnlm-yiddish-language-model-evaluation/)
295. **[Measuring Distribution Shift in User Prompts and Its Effects on LLM Performance](https://md.research.elamur.ai/free/en/papers/seegmiller-2026-measuring-distribution-shift-user-prompts/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Parker Seegmiller, Sarah Masud Preum*2026*
296. **[Merge and Conquer: Instructing Multilingual Models by Adding Target Language Weights](https://md.research.elamur.ai/free/en/papers/valero-2026-merge-conquer-instructing-multilingual-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Eneko Valero, Maria Ribalta i Albado, Oscar Sainz, et al.*2026*
297. **[MUC-4 Revisited: Document-level Event Analysis beyond Span-based Arguments](https://md.research.elamur.ai/free/en/papers/olsen-2026-muc-4-revisited-document-level/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Helene Bøsei Olsen, Erik Velldal, Lilja Øvrelid*2026*
298. **[MUTANT: A Recipe for Multilingual Tokenizer Design](https://md.research.elamur.ai/free/en/papers/rana-2026-mutant-recipe-multilingual-tokenizer-design/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Souvik Rana, Ashish Kulkarni, Arul Menezes, et al.*2026*
299. **[M³-VQA: A Benchmark for Multimodal, Multi-Entity, Multi-Hop Visual Question Answering](https://md.research.elamur.ai/free/en/papers/ma-2026-m-3-vqa-benchmark-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiatong Ma, Longteng Guo, Yuchen Liu, et al.*2026*
300. **[NegNLI-BR: A Brazilian Portuguese Benchmark for Negation in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/westhelle-2026-negnli-br-brazilian-portuguese-benchmark/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Matheus Westhelle, Viviane Moreira*2026*

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