---
title: "Who cites Aman Rangapur — 408 papers of our library"
description: "408 papers of the Elamur Research library cite the works of Aman Rangapur, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
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# Who cites Aman Rangapur

432 citations of their works from 408 papers of our library (of the 149,439 whose bibliographies we read) · 115 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Aman Rangapur](https://md.research.elamur.ai/free/en/authors/aman-rangapur/)

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1. **[DataComp-LM: In search of the next generation of training sets for language models](https://md.research.elamur.ai/free/en/papers/li-2024-datacomp-lm-search-next-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.*2024 · 191 citations*
2. [**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/)
3. [**SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines arXiv:2502.14739**M-A-P Team, Xinrun Du, Yifan Yao, et al.*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-supergpqa-scaling-llm-evaluation-across/)
4. [**LLMs Get Lost In Multi-Turn Conversation arXiv:2505.06120**Philippe Laban, Hiroaki Hayashi, Yingbo Zhou, et al.*2025 · 82 citations*](https://md.research.elamur.ai/free/en/papers/laban-2025-llms-get-lost-multi-turn/)
5. [**Reinforcement Learning via Self-Distillation arXiv:2601.20802**Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.*2026 · 74 citations*](https://md.research.elamur.ai/free/en/papers/hubotter-2026-reinforcement-learning-self-distillation/)
6. **[Generalizing Verifiable Instruction Following](https://md.research.elamur.ai/free/en/papers/pyatkin-2025-generalizing-verifiable-instruction-following/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Valentina Pyatkin, Saumya Malik, Victoria Graf, et al.*2025 · 59 citations*
7. [**mmBERT: A Modern Multilingual Encoder with Annealed Language Learning arXiv:2509.06888**Marc Marone, Orion Weller, William Fleshman, et al.*2025 · 59 citations*](https://md.research.elamur.ai/free/en/papers/marone-2025-mmbert-modern-multilingual-encoder-annealed/)
8. [**DeepSeek-OCR: Contexts Optical Compression arXiv:2510.18234**Haoran Wei, Yaofeng Sun, Yukun Li*2025 · 54 citations*](https://md.research.elamur.ai/free/en/papers/wei-2025-deepseek-ocr-contexts-optical/)
9. [**Spurious Rewards: Rethinking Training Signals in RLVR arXiv:2506.10947**Rulin Shao, Shuyue Stella Li, Rui Xin, et al.*2025 · 53 citations*](https://md.research.elamur.ai/free/en/papers/shao-2025-spurious-rewards-rethinking-training-signals/)
10. [**Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy arXiv:2507.01352**Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, et al.*2025 · 48 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-skywork-reward-v2-scaling/)
11. [**EuroLLM-9B: Technical Report arXiv:2506.04079**Pedro Henrique Martins, Joao Alves, Patrick Fernandes, et al.*2025 · 45 citations*](https://md.research.elamur.ai/free/en/papers/martins-2025-eurollm-9b-technical-report/)
12. [**olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language Models arXiv:2502.18443**Jake Poznanski, Aman Rangapur, Jon Borchardt, et al.*2025 · 44 citations*](https://md.research.elamur.ai/free/en/papers/poznanski-2025-olmocr-unlocking-trillions-tokens-pdfs/)
13. **[Checklists Are Better Than Reward Models For Aligning Language Models](https://md.research.elamur.ai/free/en/papers/viswanathan-2025-checklists-better-than-reward-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Vijay Viswanathan, Yanchao Sun, Shuang Ma, et al.*2025 · 37 citations*
14. **[MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing](https://md.research.elamur.ai/free/en/papers/niu-2026-mineru2-5-decoupled-vision-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junbo Niu, Zheng Liu, Zhuangcheng Gu, et al.*2026 · 35 citations*
15. [**EuroBERT: Scaling Multilingual Encoders for European Languages arXiv:2503.05500**Nicolas Boizard, Hippolyte Gisserot-Boukhlef, Duarte M. Alves, et al.*2025 · 34 citations*](https://md.research.elamur.ai/free/en/papers/boizard-2025-eurobert-scaling-multilingual-encoders-european/)
16. **[Linguistic Generalizability of Test-Time Scaling in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/son-2025-linguistic-generalizability-test-time-scaling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guijin Son, Jiwoo Hong, Hyunwoo Ko, et al.*2025 · 24 citations*
17. **[IssueBench: Millions of Realistic Prompts for Measuring Issue Bias in LLM Writing Assistance](https://md.research.elamur.ai/free/en/papers/rottger-2026-issuebench-millions-realistic-prompts-measuring/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Paul Röttger, Musashi Hinck, Valentin Hofmann, et al.*2026 · 16 citations*
18. [**Rethinking Reflection in Pre-Training arXiv:2504.04022**Essential AI: Darsh J Shah, Peter Rushton, Somanshu Singla, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/shah-2025-rethinking-reflection-pre-training/)
19. **[ToDi: Token-wise Distillation via Fine-Grained Divergence Control](https://md.research.elamur.ai/free/en/papers/jung-2025-todi-token-wise-distillation-fine/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Seongryong Jung, Suwan Yoon, DongGeon Kim, et al.*2025 · 12 citations*
20. [**Cross-lingual Collapse: How Language-Centric Foundation Models Shape Reasoning in Large Language Models arXiv:2506.05850**Cheonbok Park; Jeonghoon Kim; Joosung Lee; Sanghwan Bae; Jaegul Choo;, Kang Min Yoo*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/park-2025-cross-lingual-collapse-language-centric/)
21. **[Between Circuits and Chomsky: Pre-pretraining on Formal Languages Imparts Linguistic Biases](https://md.research.elamur.ai/free/en/papers/hu-2025-between-circuits-chomsky-pre-pretraining/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michael Y. Hu, Jackson Petty, Chuan Shi, et al.*2025 · 9 citations*
22. [**Language Models Fail to Introspect About Their Knowledge of Language arXiv:2503.07513**Siyuan Song, Jennifer Hu, Kyle Mahowald*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/song-2025-language-models-fail-introspect-about/)
23. **[Structured Moral Reasoning in Language Models: A Value-Grounded Evaluation Framework](https://md.research.elamur.ai/free/en/papers/chakraborty-2025-structured-moral-reasoning-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mohna Chakraborty, Lu Wang, David Jurgens*2025 · 9 citations*
24. **[TESS 2: A Large-Scale Generalist Diffusion Language Model](https://md.research.elamur.ai/free/en/papers/tae-2025-tess-2-large-scale-generalist/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jaesung Tae, Hamish Ivison, Sachin Kumar, et al.*2025 · 9 citations*
25. **[Theorem Prover as a Judge for Synthetic Data Generation](https://md.research.elamur.ai/free/en/papers/leang-2025-theorem-prover-as-judge-synthetic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joshua Ong Jun Leang, Giwon Hong, Wenda Li, et al.*2025 · 9 citations*
26. [**DeepSeek-OCR 2: Visual Causal Flow arXiv:2601.20552**Haoran Wei, Yaofeng Sun, Yukun Li*2026 · 8 citations*](https://md.research.elamur.ai/free/en/papers/wei-2026-deepseek-ocr-2-visual/)
27. **[MetaScale: Test-Time Scaling with Evolving Meta-Thoughts](https://md.research.elamur.ai/free/en/papers/liu-2026-metascale-test-time-scaling-evolving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qin Liu, Wenxuan Zhou, Nan Xu, et al.*2026 · 7 citations*
28. [**Pushing on Multilingual Reasoning Models with Language-Mixed Chain-of-Thought arXiv:2510.04230**Guijin Son, Donghun Yang, Hitesh Laxmichand Patel, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/son-2025-pushing-multilingual-reasoning-models-language/)
29. **[Why Supervised Fine-Tuning Fails to Learn: A Systematic Study of Incomplete Learning in Large Language Models](https://md.research.elamur.ai/free/en/papers/xue-2026-why-supervised-fine-tuning-fails/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chao Xue, Yao Wang, Mengqiao Liu, et al.*2026 · 6 citations*
30. **[MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs](https://md.research.elamur.ai/free/en/papers/liu-2025-metafaith-faithful-natural-language-uncertainty/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gabrielle Kaili-May Liu, Gal Yona, Avi Caciularu, et al.*2025 · 6 citations*
31. **[Sparse Logit Sampling: Accelerating Knowledge Distillation in LLMs](https://md.research.elamur.ai/free/en/papers/anshumann-2025-sparse-logit-sampling-accelerating-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Anshumann, Mohd Abbas Zaidi, Akhil Kedia, et al.*2025 · 6 citations*
32. [**GLM-OCR Technical Report arXiv:2603.10910**Shuaiqi Duan, Yadong Xue, Weihan Wang, et al.*2026 · 4 citations*](https://md.research.elamur.ai/free/en/papers/duan-2026-glm-ocr-technical-report/)
33. **[Infinity-Parser: Layout-Aware Reinforcement Learning with High-quality Document Parsing Dataset](https://md.research.elamur.ai/free/en/papers/wang-2026-infinity-parser-layout-aware-reinforcement/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Baode Wang, Biao Wu, Weizhen Li, et al.*2026 · 4 citations*
34. **[ProFit: Leveraging High-Value Signals in SFT via Probability-Guided Token Selection](https://md.research.elamur.ai/free/en/papers/liu-2026-profit-leveraging-high-value-signals/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tao Liu, Taiqiang Wu, Runming Yang, et al.*2026 · 4 citations*
35. **[Agentic Rubrics as Contextual Verifiers for SWE Agents](https://md.research.elamur.ai/free/en/papers/raghavendra-2026-agentic-rubrics-as-contextual-verifiers/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohit Raghavendra, Anisha Gunjal, Bing Liu, et al.*2026 · 3 citations*
36. **[Explaining Sources of Uncertainty in Automated Fact-Checking](https://md.research.elamur.ai/free/en/papers/sun-2026-explaining-sources-uncertainty-automated-fact/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingyi Sun, Greta Warren, Irina Shklovski, et al.*2026 · 3 citations*
37. **[Language Statistics and False Belief Reasoning: Evidence from 41 Open-Weight LMs](https://md.research.elamur.ai/free/en/papers/trott-2026-language-statistics-false-belief-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sean Trott, Samuel M. Taylor, Cameron Robert Jones, et al.*2026 · 3 citations*
38. **[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*
39. **[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*
40. **[VeriTaS: The First Dynamic Benchmark for Multimodal Automated Fact-Checking](https://md.research.elamur.ai/free/en/papers/rothermel-2026-veritas-first-dynamic-benchmark-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mark Rothermel, Marcus Kornmann, Marcus Rohrbach, et al.*2026 · 3 citations*
41. [**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/)
42. **[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*
43. **[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*
44. **[LiveFact: A Dynamic, Time-Aware Benchmark for LLM-Driven Fake News Detection](https://md.research.elamur.ai/free/en/papers/xu-2026-livefact-dynamic-time-aware-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Cheng Xu, Changhong Jin, Yingjie Niu, et al.*2026 · 2 citations*
45. **[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*
46. **[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*
47. **[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*
48. **[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*
49. [**STEP3-VL-10B Technical Report arXiv:2601.09668**Ailin Huang, Chengyuan Yao, Chunrui Han, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/huang-2026-step3-vl-10b-technical/)
50. **[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*
51. [**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/)
52. **[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*
53. **[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*
54. **[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*
55. **[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*
56. **[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*
57. **[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*
58. **[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*
59. **[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*
60. [**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/)
61. **[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*
62. **[MEVER: Multi-Modal and Explainable Claim Verification with Graph-based Evidence Retrieval](https://md.research.elamur.ai/free/en/papers/zhang-2026-mever-multi-modal-explainable-claim/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Delvin Ce Zhang, Suhan Cui, Zhelin Chu, et al.*2026 · 1 citation*
63. **[OCRTurk: A Comprehensive OCR Benchmark for Turkish](https://md.research.elamur.ai/free/en/papers/yilmaz-2026-ocrturk-comprehensive-ocr-benchmark-turkish/) [Workshop Natural Language Processing for Turkic Languages](https://md.research.elamur.ai/free/en/venues/sigturk/)**Deniz Yılmaz, Evren Ayberk Munis, Cagri Toraman, et al.*2026 · 1 citation*
64. **[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*
65. **[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*
66. **[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*
67. **[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*
68. **[SCAN: Semantic Document Layout Analysis for Textual and Visual Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/ueda-2026-scan-semantic-document-layout-analysis/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nobuhiro Ueda, Yuyang Dong, Krisztián Boros, et al.*2026 · 1 citation*
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80. **[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*
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