---
title: "Who cites Chatbot Arena: An Open — 446 citing papers"
description: "446 papers of the Elamur Research library cite «Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference», found in their…"
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---
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# Who cites «Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference»

446 papers of our library cite it (of the 149,439 whose bibliographies we read) · 97 with a page here, the most cited first · [← back to «Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference»](https://md.research.elamur.ai/free/en/papers/chiang-2024-chatbot-arena-open-platform-evaluating/)

1. [**The Llama 3 Herd of Models arXiv:2407.21783**Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.*2024 · 7,682 citations*](https://md.research.elamur.ai/free/en/papers/grattafiori-2024-llama-3-herd-models/)
2. **[DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2025-deepseek-r1-incentivizing-reasoning-capability/) [Nature](https://md.research.elamur.ai/free/en/venues/nature/)**DeepSeek-AI, Daya Guo, Dejian Yang, et al.*2025 · 4,728 citations*
3. [**Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities arXiv:2507.06261**Gheorghe Comanici, Eric Bieber, Mike Schaekermann, et al.*2025 · 974 citations*](https://md.research.elamur.ai/free/en/papers/comanici-2025-gemini-2-5-pushing-frontier/)
4. **[MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/wang-2024-mmlu-pro-more-robust-challenging/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yubo Wang, Xueguang Ma, Ge Zhang, et al.*2024 · 761 citations*
5. **[SGLang: Efficient Execution of Structured Language Model Programs](https://md.research.elamur.ai/free/en/papers/zheng-2023-sglang-efficient-execution-structured-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, et al.*2023 · 729 citations*
6. [**Qwen2.5-Coder Technical Report arXiv:2409.12186**Binyuan Hui, Jian Yang, Zeyu Cui, et al.*2024 · 559 citations*](https://md.research.elamur.ai/free/en/papers/hui-2024-qwen2-5-coder-technical-report/)
7. **[SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering](https://md.research.elamur.ai/free/en/papers/yang-2024-swe-agent-agent-computer-interfaces/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**John Yang, Carlos E. Jimenez, Alexander Wettig, et al.*2024 · 552 citations*
8. [**Phi-4 Technical Report arXiv:2412.08905**Marah Abdin, Jyoti Aneja, Harkirat Behl, et al.*2024 · 502 citations*](https://md.research.elamur.ai/free/en/papers/abdin-2024-phi-4-technical-report/)
9. [**Tulu 3: Pushing Frontiers in Open Language Model Post-Training arXiv:2411.15124**Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.*2024 · 423 citations*](https://md.research.elamur.ai/free/en/papers/lambert-2024-tulu-3-pushing-frontiers-open/)
10. **[Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models](https://md.research.elamur.ai/free/en/papers/deitke-2024-molmo-pixmo-open-weights-open/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Matt Deitke, Christopher Clark, Sangho Lee, et al.*2024 · 216 citations*
11. [**From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline arXiv:2406.11939**Tianle Li, Wei-Lin Chiang, Evan Frick, et al.*2024 · 210 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-crowdsourced-data-high-quality-benchmarks/)
12. **[Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/tong-2024-cambrian-1-fully-open-vision/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shengbang Tong, Ellis Brown, Penghao Wu, et al.*2024 · 208 citations*
13. [**Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models arXiv:2410.07985**Bofei Gao, Feifan Song, Zhe Yang, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-omni-math-universal-olympiad-level/)
14. [**LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks arXiv:2406.18403**Anna Bavaresco, Raffaella Bernardi, Leonardo Bertolazzi, et al.*2024 · 141 citations*](https://md.research.elamur.ai/free/en/papers/bavaresco-2024-llms-instead-human-judges-large/)
15. **[LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-lmms-eval-reality-check-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaichen Zhang, Bo Li, Peiyuan Zhang, et al.*2025 · 115 citations*
16. [**WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild arXiv:2406.04770**Bill Yuchen Lin, Yuntian Deng, Khyathi Chandu, et al.*2024 · 105 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-wildbench-benchmarking-llms-challenging-tasks/)
17. [**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/)
18. **[AudioBench: A Universal Benchmark for Audio Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-audiobench-universal-benchmark-audio-large/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bin Wang, Xunlong Zou, Geyu Lin, et al.*2025 · 77 citations*
19. **[KMMLU: Measuring Massive Multitask Language Understanding in Korean](https://md.research.elamur.ai/free/en/papers/son-2025-kmmlu-measuring-massive-multitask-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Guijin Son, Hanwool Lee, Sungdong Kim, et al.*2025 · 76 citations*
20. [**MagicPIG: LSH Sampling for Efficient LLM Generation arXiv:2410.16179**Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, et al.*2024 · 68 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-magicpig-lsh-sampling-efficient-llm/)
21. [**RM-Bench: Benchmarking Reward Models of Language Models with Subtlety and Style arXiv:2410.16184**Yantao Liu, Zijun Yao, Rui Min, et al.*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-rm-bench-benchmarking-reward-models/)
22. **[Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback](https://md.research.elamur.ai/free/en/papers/ivison-2024-unpacking-dpo-ppo-disentangling-best/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hamish Ivison, Yizhong Wang, Jiacheng Liu, et al.*2024 · 50 citations*
23. **[MixEval: Deriving Wisdom of the Crowd from LLM Benchmark Mixtures](https://md.research.elamur.ai/free/en/papers/ni-2024-mixeval-deriving-wisdom-crowd-llm/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jinjie Ni, Fuzhao Xue, Xiang Yue, et al.*2024 · 47 citations*
24. **[FollowIR: Evaluating and Teaching Information Retrieval Models to Follow Instructions](https://md.research.elamur.ai/free/en/papers/weller-2025-followir-evaluating-teaching-information-retrieval/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Orion Weller, Benjamin Chang, Sean MacAvaney, et al.*2025 · 40 citations*
25. [**Observational Scaling Laws and the Predictability of Language Model Performance arXiv:2405.10938**Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto*2024 · 40 citations*](https://md.research.elamur.ai/free/en/papers/ruan-2024-observational-scaling-laws-predictability-language/)
26. **[CulturalBench: A Robust, Diverse and Challenging Benchmark for Measuring LMs' Cultural Knowledge Through Human-AI Red-Teaming](https://md.research.elamur.ai/free/en/papers/chiu-2025-culturalbench-robust-diverse-challenging-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Ying Chiu, Liwei Jiang, Bill Yuchen Lin, et al.*2025 · 38 citations*
27. [**SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety arXiv:2404.05399**Paul Rottger, Fabio Pernisi, Bertie Vidgen, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2024-safetyprompts-systematic-review-open-datasets/)
28. **[Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Above](https://md.research.elamur.ai/free/en/papers/balepur-2025-which-these-best-describes-multiple/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nishant Balepur, Rachel Rudinger, Jordan Boyd-Graber*2025 · 28 citations*
29. [**Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning arXiv:2512.20848**NVIDIA: Aaron Blakeman, Aaron Grattafiori, Aarti Basant, et al.*2025 · 27 citations*](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-3-nano-open-efficient/)
30. [**LLM-as-a-Judge & Reward Model: What They Can and Cannot Do arXiv:2409.11239**Guijin Son, Hyunwoo Ko, Hoyoung Lee, et al.*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/son-2024-llm-judge-reward-model-they/)
31. [**Language Model Alignment in Multilingual Trolley Problems arXiv:2407.02273**Zhijing Jin, Max Kleiman-Weiner, Giorgio Piatti, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/jin-2024-language-model-alignment-multilingual-trolley/)
32. [**Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation arXiv:2410.02725**Rohin Manvi, Anikait Singh, Stefano Ermon*2024 · 22 citations*](https://md.research.elamur.ai/free/en/papers/manvi-2024-adaptive-inference-time-compute-llms/)
33. **[“Give Me BF16 or Give Me Death”? Accuracy-Performance Trade-Offs in LLM Quantization](https://md.research.elamur.ai/free/en/papers/kurtic-2025-give-me-bf16-or-give/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Eldar Kurtic, Alexandre Noll Marques, Shubhra Pandit, et al.*2025 · 21 citations*
34. **[Anchored Preference Optimization and Contrastive Revisions: Addressing Underspecification in Alignment](https://md.research.elamur.ai/free/en/papers/oosterlinck-2025-anchored-preference-optimization-contrastive-revisions/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Karel D'Oosterlinck, Winnie Xu, Chris Develder, et al.*2025 · 20 citations*
35. **[CRAFT Your Dataset: Task-Specific Synthetic Dataset Generation Through Corpus Retrieval and Augmentation](https://md.research.elamur.ai/free/en/papers/ziegler-2025-craft-your-dataset-task-specific/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ingo Ziegler, Abdullatif Köksal, Desmond Elliott, et al.*2025 · 20 citations*
36. [**GameBench: Evaluating Strategic Reasoning Abilities of LLM Agents arXiv:2406.06613**Anthony Costarelli, Mat Allen, Roman Hauksson, et al.*2024 · 20 citations*](https://md.research.elamur.ai/free/en/papers/costarelli-2024-gamebench-evaluating-strategic-reasoning-abilities/)
37. **[Navigating Rifts in Human-LLM Grounding: Study and Benchmark](https://md.research.elamur.ai/free/en/papers/shaikh-2025-navigating-rifts-human-llm-grounding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Omar Shaikh, Hussein Mozannar, Gagan Bansal, et al.*2025 · 19 citations*
38. [**sDPO: Don't Use Your Data All at Once arXiv:2403.19270**Dahyun Kim, Yungi Kim, Wonho Song, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/kim-2024-sdpo-don-t-use-data/)
39. [**Vibe-Eval: A hard evaluation suite for measuring progress of multimodal language models arXiv:2405.02287**Piotr Padlewski, Max Bain, Matthew Henderson, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/padlewski-2024-vibe-eval-hard-evaluation-suite/)
40. **[Towards Holistic Evaluation of Large Audio-Language Models: A Comprehensive Survey](https://md.research.elamur.ai/free/en/papers/yang-2025-holistic-evaluation-large-audio-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chih-Kai Yang, Neo S. Ho, Hung-yi Lee*2025 · 17 citations*
41. [**MultiPragEval: Multilingual Pragmatic Evaluation of Large Language Models Proceedings of the 2nd GenBench Workshop on Generalisation (Benchmarking) in NLP**Dojun Park, Jiwoo Lee, Seohyun Park, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/park-2024-multiprageval-multilingual-pragmatic-evaluation-large/)
42. [**Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation arXiv:2603.19220**Zhuolin Yang, Zihan Liu, Yang Chen, et al.*2026 · 16 citations*](https://md.research.elamur.ai/free/en/papers/yang-2026-nemotron-cascade-2-post-training/)
43. **[Auto-Arena: Automating LLM Evaluations with Agent Peer Battles and Committee Discussions](https://md.research.elamur.ai/free/en/papers/zhao-2025-auto-arena-automating-llm-evaluations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruochen Zhao, Wenxuan Zhang, Yew Ken Chia, et al.*2025 · 16 citations*
44. **[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*
45. **[MIRAGE-Bench: Automatic Multilingual Benchmark Arena for Retrieval-Augmented Generation Systems](https://md.research.elamur.ai/free/en/papers/thakur-2025-mirage-bench-automatic-multilingual-benchmark/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nandan Thakur, Suleman Kazi, Ge Luo, et al.*2025 · 15 citations*
46. **[When One LLM Drools, Multi-LLM Collaboration Rules](https://md.research.elamur.ai/free/en/papers/feng-2026-when-one-llm-drools-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shangbin Feng, Wenxuan Ding, Alisa Liu, et al.*2026 · 14 citations*
47. **[BALSAM: A Platform for Benchmarking Arabic Large Language Models](https://md.research.elamur.ai/free/en/papers/matham-2025-balsam-platform-benchmarking-arabic-large/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Rawan Al-Matham, Kareem Darwish, Raghad Al-Rasheed, et al.*2025 · 14 citations*
48. **[MTSA: Multi-turn Safety Alignment for LLMs through Multi-round Red-teaming](https://md.research.elamur.ai/free/en/papers/guo-2025-mtsa-multi-turn-safety-alignment/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weiyang Guo, Jing Li, Wenya Wang, et al.*2025 · 14 citations*
49. **[TripleFact: Defending Data Contamination in the Evaluation of LLM-driven Fake News Detection](https://md.research.elamur.ai/free/en/papers/xu-2025-triplefact-defending-data-contamination-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Cheng Xu, Nan Yan*2025 · 12 citations*
50. **[SciArena: An Open Evaluation Platform for Non-Verifiable Scientific Literature-Grounded Tasks](https://md.research.elamur.ai/free/en/papers/zhao-2025-sciarena-open-evaluation-platform-non/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yilun Zhao, Kaiyan Zhang, Tiansheng Hu, et al.*2025 · 11 citations*
51. **[Beyond the Surface: Measuring Self-Preference in LLM Judgments](https://md.research.elamur.ai/free/en/papers/chen-2025-beyond-surface-measuring-self-preference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhi-Yuan Chen, Hao Wang, Xinyu Zhang, et al.*2025 · 10 citations*
52. [**Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought arXiv:2505.15431**Tencent Hunyuan Team, Ao Liu, Botong Zhou, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-hunyuan-hunyuan-turbos-advancing-large/)
53. **[Too Late to Train, Too Early To Use? A Study on Necessity and Viability of Low-Resource Bengali LLMs](https://md.research.elamur.ai/free/en/papers/mahfuz-2025-too-late-train-too-early/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Tamzeed Mahfuz, Satak Kumar Dey, Ruwad Naswan, et al.*2025 · 10 citations*
54. **[ChatBench: From Static Benchmarks to Human-AI Evaluation](https://md.research.elamur.ai/free/en/papers/chang-2025-chatbench-static-benchmarks-human-ai/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Serina Chang, Ashton Anderson, Jake M. Hofman*2025 · 9 citations*
55. **[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*
56. **[Sentient Agent as a Judge: Evaluating Higher-Order Social Cognition in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-sentient-agent-as-judge-evaluating/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bang Zhang, Ruotian Ma, Qingxuan Jiang, et al.*2026 · 6 citations*
57. [**mR3: Multilingual Rubric-Agnostic Reward Reasoning Models arXiv:2510.01146**David Anugraha, Shou-Yi Hung, Zilu Tang, et al.*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/anugraha-2025-mr3-multilingual-rubric-agnostic-reward/)
58. [**GemmAr: Enhancing LLMs Through Arabic Instruction-Tuning arXiv:2407.02147**Hasna Chouikhi, Manel Aloui, Cyrine Ben Hammou, et al.*2024 · 4 citations*](https://md.research.elamur.ai/free/en/papers/chouikhi-2024-gemmar-enhancing-llms-through-arabic/)
59. **[How Long Reasoning Chains Influence LLMs' Judgment of Answer Factuality](https://md.research.elamur.ai/free/en/papers/tu-2026-how-long-reasoning-chains-influence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minzhu Tu, Shiyu Ni, Keping Bi*2026 · 3 citations*
60. **[LLMEval-Fair: A Large-Scale Longitudinal Study on Robust and Fair Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-llmeval-fair-large-scale-longitudinal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ming Zhang, Yujiong Shen, Jingyi Deng, et al.*2026 · 3 citations*
61. **[My LLM might Mimic AAE - But When Should It?](https://md.research.elamur.ai/free/en/papers/sandoval-2025-my-llm-might-mimic-aae/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sandra Camille Sandoval, Christabel Acquaye, Kwesi Adu Cobbina, et al.*2025 · 3 citations*
62. **[EvoRoute: Experience-Driven Self-Routing LLM Agent Systems](https://md.research.elamur.ai/free/en/papers/zhang-2026-evoroute-experience-driven-self-routing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guibin Zhang, Haiyang Yu, Kaiming Yang, et al.*2026 · 2 citations*
63. **[Paragraph Segmentation Revisited: Towards a Standard Task for Structuring Speech](https://md.research.elamur.ai/free/en/papers/retkowski-2026-paragraph-segmentation-revisited-standard-task/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Fabian Retkowski, Alexander Waibel*2026 · 2 citations*
64. **[Position: LLM Watermarking Should Align Stakeholders' Incentives for Practical Adoption](https://md.research.elamur.ai/free/en/papers/liu-2026-position-llm-watermarking-should-align/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yepeng Liu, Xuandong Zhao, Dawn Song, et al.*2026 · 2 citations*
65. [**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/)
66. **[Tracking the evolution of LLM capabilities for Belarusian with OpenAI Evals](https://md.research.elamur.ai/free/en/papers/poritski-2026-tracking-evolution-llm-capabilities-belarusian/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Vladislav Poritski, Oksana Volchek, Maksim Aparovich, et al.*2026 · 2 citations*
67. [**WASIL: In-the-Wild Arabic Spoken Interactions with LLMs arXiv:2605.16364**Zien Sheikh Ali, Hamdy Mubarak, Soon-Gyo Jung, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/ali-2026-wasil-wild-arabic-spoken-interactions/)
68. [**Methodology of Adapting Large English Language Models for Specific Cultural Contexts arXiv:2406.18192**Wenjing Zhang, Siqi Xiao, Xuejiao Lei, et al.*2024 · 2 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-methodology-adapting-large-english-language/)
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