---
title: "Who cites Yuan-Fang Li — 367 papers of our library"
description: "367 papers of the Elamur Research library cite the works of Yuan-Fang Li, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/yuan-fang-li/cited-by/"
---
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# Who cites Yuan-Fang Li

367 citations of their works from 367 papers of our library (of the 149,439 whose bibliographies we read) · 75 with a page here, the most cited first · [← Yuan-Fang Li](https://md.research.elamur.ai/free/en/authors/yuan-fang-li/)

1. [**Gemini: A Family of Highly Capable Multimodal Models arXiv:2312.11805**Gemini Team, Rohan Anil, Sebastian Borgeaud, et al.*2023 · 3,050 citations*](https://md.research.elamur.ai/free/en/papers/gemini-team-2023-gemini-family-highly-capable-multimodal/)
2. [**PaLM 2 Technical Report arXiv:2305.10403**Rohan Anil, Andrew M. Dai, Orhan Firat, et al.*2023 · 1,000 citations*](https://md.research.elamur.ai/free/en/papers/anil-2023-palm-2-technical-report/)
3. [**Crosslingual Generalization through Multitask Finetuning arXiv:2211.01786**Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.*2022 · 703 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-crosslingual-generalization-through-multitask-finetuning/)
4. **[ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning](https://md.research.elamur.ai/free/en/papers/lai-2023-chatgpt-beyond-english-comprehensive-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Viet Dac Lai, Nghia Ngo, Amir Pouran Ben Veyseh, et al.*2023 · 422 citations*
5. [**MEGA: Multilingual Evaluation of Generative AI arXiv:2303.12528**Kabir Ahuja, Harshita Diddee, Rishav Hada, et al.*2023 · 285 citations*](https://md.research.elamur.ai/free/en/papers/ahuja-2023-mega-multilingual-evaluation-generative-ai/)
6. **[The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants](https://md.research.elamur.ai/free/en/papers/bandarkar-2023-belebele-benchmark-parallel-reading-comprehension/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lucas Bandarkar, Davis Liang, Benjamin Muller, et al.*2023 · 262 citations*
7. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model arXiv:2402.07827**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 253 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/)
8. [**Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought Prompting arXiv:2305.07004**Haoyang Huang, Tianyi Tang, Dongdong Zhang, et al.*2023 · 224 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-all-languages-created-equal-llms/)
9. **[Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning](https://md.research.elamur.ai/free/en/papers/singh-2024-aya-dataset-open-access-collection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shivalika Singh, Freddie Vargus, Daniel D'souza, et al.*2024 · 207 citations*
10. **[Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Models](https://md.research.elamur.ai/free/en/papers/ahia-2023-do-all-languages-cost-same/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Orevaoghene Ahia, Sachin Kumar, Hila Gonen, et al.*2023 · 174 citations*
11. [**Aya 23: Open Weight Releases to Further Multilingual Progress arXiv:2405.15032**Viraat Aryabumi, John Dang, Dwarak Talupuru, et al.*2024 · 172 citations*](https://md.research.elamur.ai/free/en/papers/aryabumi-2024-aya-23-open-weight-releases/)
12. [**ShortGPT: Layers in Large Language Models are More Redundant Than You Expect arXiv:2403.03853**Xin Men, Mingyu Xu, Qingyu Zhang, et al.*2024 · 169 citations*](https://md.research.elamur.ai/free/en/papers/men-2024-shortgpt-layers-large-language-models/)
13. **[Many-Shot In-Context Learning](https://md.research.elamur.ai/free/en/papers/agarwal-2024-many-shot-context-learning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.*2024 · 142 citations*
14. **[IndicBART: A Pre-trained Model for Indic Natural Language Generation](https://md.research.elamur.ai/free/en/papers/dabre-2022-indicbart-pre-trained-model-indic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Raj Dabre, Himani Shrotriya, Anoop Kunchukuttan, et al.*2022 · 141 citations*
15. **[GlotLID: Language Identification for Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/kargaran-2023-glotlid-language-identification-low-resource/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Amir Hossein Kargaran, Ayyoob Imani, François Yvon, et al.*2023 · 116 citations*
16. [**Continual Pre-Training for Cross-Lingual LLM Adaptation: Enhancing Japanese Language Capabilities arXiv:2404.17790**Kazuki Fujii, Taishi Nakamura, Mengsay Loem, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/fujii-2024-continual-pre-training-cross-lingual/)
17. **[GPTAraEval: A Comprehensive Evaluation of ChatGPT on Arabic NLP](https://md.research.elamur.ai/free/en/papers/khondaker-2023-gptaraeval-comprehensive-evaluation-chatgpt-arabic/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tawkat Islam Khondaker, Abdul Waheed, El Moatez Billah Nagoudi, et al.*2023 · 110 citations*
18. **[TrueTeacher: Learning Factual Consistency Evaluation with Large Language Models](https://md.research.elamur.ai/free/en/papers/gekhman-2023-trueteacher-learning-factual-consistency-evaluation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zorik Gekhman, Jonathan Herzig, Roee Aharoni, et al.*2023 · 106 citations*
19. **[How do Large Language Models Handle Multilingualism?](https://md.research.elamur.ai/free/en/papers/zhao-2024-large-language-models-handle-multilingualism/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yiran Zhao, Wenxuan Zhang, Guizhen Chen, et al.*2024 · 102 citations*
20. **[BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer](https://md.research.elamur.ai/free/en/papers/asai-2024-buffet-benchmarking-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Akari Asai, Sneha Kudugunta, Xinyan Yu, et al.*2024 · 86 citations*
21. **[WMT24++: Expanding the Language Coverage of WMT24 to 55 Languages & Dialects](https://md.research.elamur.ai/free/en/papers/deutsch-2025-wmt24-expanding-language-coverage-wmt24/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Daniel Deutsch, Eleftheria Briakou, Isaac Rayburn Caswell, et al.*2025 · 80 citations*
22. **[AraBART: a Pretrained Arabic Sequence-to-Sequence Model for Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/eddine-2022-arabart-pretrained-arabic-sequence-sequence/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Moussa Kamal Eddine, Nadi Tomeh, Nizar Habash, et al.*2022 · 80 citations*
23. **[MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks](https://md.research.elamur.ai/free/en/papers/ahuja-2024-megaverse-benchmarking-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sanchit Ahuja, Divyanshu Aggarwal, Varun Gumma, et al.*2024 · 74 citations*
24. [**Revolutionizing Finance with LLMs: An Overview of Applications and Insights arXiv:2401.11641**Huaqin Zhao, Zhengliang Liu, Zihao Wu, et al.*2024 · 63 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2024-revolutionizing-finance-llms-overview-applications/)
25. [**Exploring the Benefits of Training Expert Language Models over Instruction Tuning arXiv:2302.03202**Joel Jang, Seungone Kim, Seonghyeon Ye, et al.*2023 · 63 citations*](https://md.research.elamur.ai/free/en/papers/jang-2023-exploring-benefits-training-expert-language/)
26. **[Is Translation All You Need? A Study on Solving Multilingual Tasks with Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2025-is-translation-all-you-need/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chaoqun Liu, Wenxuan Zhang, Yiran Zhao, et al.*2025 · 61 citations*
27. **[An Open Dataset and Model for Language Identification](https://md.research.elamur.ai/free/en/papers/burchell-2023-open-dataset-model-language-identification/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Laurie Burchell, Alexandra Birch, Nikolay Bogoychev, et al.*2023 · 60 citations*
28. **[SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages](https://md.research.elamur.ai/free/en/papers/lovenia-2024-seacrowd-multilingual-multimodal-data-hub/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Holy Lovenia, Rahmad Mahendra, Salsabil Maulana Akbar, et al.*2024 · 54 citations*
29. [**LLM Pruning and Distillation in Practice: The Minitron Approach arXiv:2408.11796**Sharath Turuvekere Sreenivas, Saurav Muralidharan, Raviraj Joshi, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/sreenivas-2024-llm-pruning-distillation-practice-minitron/)
30. **[Should We Ban English NLP for a Year?](https://md.research.elamur.ai/free/en/papers/sogaard-2022-should-we-ban-english-nlp/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Anders Søgaard*2022 · 38 citations*
31. **[Dolphin: A Challenging and Diverse Benchmark for Arabic NLG](https://md.research.elamur.ai/free/en/papers/nagoudi-2023-dolphin-challenging-diverse-benchmark-arabic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**El Moatez Billah Nagoudi, AbdelRahim Elmadany, Ahmed Oumar El-Shangiti, et al.*2023 · 35 citations*
32. [**BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language Models arXiv:2309.06085**Wei Qi Leong, Jian Gang Ngui, Yosephine Susanto, et al.*2023 · 33 citations*](https://md.research.elamur.ai/free/en/papers/leong-2023-bhasa-holistic-southeast-asian-linguistic/)
33. **[Benchmarking Linguistic Diversity of Large Language Models](https://md.research.elamur.ai/free/en/papers/guo-2025-benchmarking-linguistic-diversity-large-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Yanzhu Guo, Guokan Shang, Chloé Clavel*2025 · 32 citations*
34. **[Enhancing Multilingual Capabilities of Large Language Models through Self-Distillation from Resource-Rich Languages](https://md.research.elamur.ai/free/en/papers/zhang-2024-enhancing-multilingual-capabilities-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanchi Zhang, Yile Wang, Zijun Liu, et al.*2024 · 30 citations*
35. [**ChartSumm: A Comprehensive Benchmark for Automatic Chart Summarization of Long and Short Summaries arXiv:2304.13620**Raian Rahman, Rizvi Hasan, Abdullah Al Farhad, et al.*2023 · 30 citations*](https://md.research.elamur.ai/free/en/papers/rahman-2023-chartsumm-comprehensive-benchmark-automatic-chart/)
36. **[Octopus: A Multitask Model and Toolkit for Arabic Natural Language Generation](https://md.research.elamur.ai/free/en/papers/elmadany-2023-octopus-multitask-model-toolkit-arabic/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**AbdelRahim Elmadany, El Moatez Billah Nagoudi, Muhammad Abdul-Mageed*2023 · 29 citations*
37. **[SensorLLM: Aligning Large Language Models with Motion Sensors for Human Activity Recognition](https://md.research.elamur.ai/free/en/papers/li-2025-sensorllm-aligning-large-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zechen Li, Shohreh Deldari, Linyao Chen, et al.*2025 · 27 citations*
38. **[IberoBench: A Benchmark for LLM Evaluation in Iberian Languages](https://md.research.elamur.ai/free/en/papers/baucells-2025-iberobench-benchmark-llm-evaluation-iberian/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Irene Baucells, Javier Aula-Blasco, Iria de-Dios-Flores, et al.*2025 · 24 citations*
39. **[Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement](https://md.research.elamur.ai/free/en/papers/kong-2025-time-mqa-time-series-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaxuan Kong, Yiyuan Yang, Yoontae Hwang, et al.*2025 · 21 citations*
40. [**Efficiently Adapting Pretrained Language Models To New Languages arXiv:2311.05741**Zoltan Csaki, Pian Pawakapan, Urmish Thakker, et al.*2023 · 21 citations*](https://md.research.elamur.ai/free/en/papers/csaki-2023-efficiently-adapting-pretrained-language-models/)
41. **[Converging to a Lingua Franca: Evolution of Linguistic Regions and Semantics Alignment in Multilingual Large Language Models](https://md.research.elamur.ai/free/en/papers/zeng-2025-converging-lingua-franca-evolution-linguistic/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Hongchuan Zeng, Senyu Han, Lu Chen, et al.*2025 · 17 citations*
42. [**Jais 2: A Family of Arabic-Centric Open Large Language Models arXiv:2608.13580**Mohamed Anwar, Abed Alhakim Freihat, George Ibrahim, et al.*2026 · 14 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2026-jais-2-family-arabic-centric/)
43. **[Benchmarking LLaMA-3 on Arabic Language Generation Tasks](https://md.research.elamur.ai/free/en/papers/khondaker-2024-benchmarking-llama-3-arabic-language/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Md Tawkat Islam Khondaker, Numaan Naeem, Fatimah Khan, et al.*2024 · 12 citations*
44. **[Synthetic Arabic Medical Dialogues Using Advanced Multi-Agent LLM Techniques](https://md.research.elamur.ai/free/en/papers/almutairi-2024-synthetic-arabic-medical-dialogues-advanced/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Mariam ALMutairi, Lulwah AlKulaib, Melike Aktas, et al.*2024 · 12 citations*
45. **[How Can We Effectively Expand the Vocabulary of LLMs with 0.01GB of Target Language Text?](https://md.research.elamur.ai/free/en/papers/yamaguchi-2026-how-can-we-effectively-expand/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Atsuki Yamaguchi, Aline Villavicencio, Nikolaos Aletras*2026 · 11 citations*
46. **[Walia-LLM: Enhancing Amharic-LLaMA by Integrating Task-Specific and Generative Datasets](https://md.research.elamur.ai/free/en/papers/azime-2024-walia-llm-enhancing-amharic-llama/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Israel Abebe Azime, Atnafu Lambebo Tonja, Tadesse Destaw Belay, et al.*2024 · 11 citations*
47. **[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*
48. **[AraHalluEval: A Fine-grained Hallucination Evaluation Framework for Arabic LLMs](https://md.research.elamur.ai/free/en/papers/alansari-2025-arahallueval-fine-grained-hallucination-evaluation/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Aisha Alansari, Hamzah Luqman*2025 · 9 citations*
49. **[On Many-Shot In-Context Learning for Long-Context Evaluation](https://md.research.elamur.ai/free/en/papers/zou-2025-many-shot-context-learning-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kaijian Zou, Muhammad Khalifa, Lu Wang*2025 · 8 citations*
50. [**HeSum: a Novel Dataset for Abstractive Text Summarization in Hebrew**Tzuf Paz-Argaman, Itai Mondshine, Asaf Achi Mordechai, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/argaman-2024-hesum-novel-dataset-abstractive-text/)
51. **[LANS: Large-scale Arabic News Summarization Corpus](https://md.research.elamur.ai/free/en/papers/alhamadani-2023-lans-large-scale-arabic-news/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Abdulaziz Alhamadani, Xuchao Zhang, Jianfeng He, et al.*2023 · 7 citations*
52. **[G2: Guided Generation for Enhanced Output Diversity in LLMs](https://md.research.elamur.ai/free/en/papers/ruan-2025-g2-guided-generation-enhanced-output/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhiwen Ruan, Yixia Li, Yefeng Liu, et al.*2025 · 6 citations*
53. **[Is Human-Like Text Liked by Humans? Multilingual Human Detection and Preference Against AI](https://md.research.elamur.ai/free/en/papers/wang-2026-is-human-like-text-liked/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxia Wang, Rui Xing, Jonibek Mansurov, et al.*2026 · 5 citations*
54. **[AraFinNews: Arabic Financial Summarisation with Domain-Adapted LLMs](https://md.research.elamur.ai/free/en/papers/el-haj-2025-arafinnews-arabic-financial-summarisation-domain/) [IEEE International Conference on Big Data (BigData)](https://md.research.elamur.ai/free/en/venues/ieee-international-conference-on-big-data-bigdata/)**Mo El-Haj, Paul Rayson*2025 · 4 citations*
55. **[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*
56. **[STReasoner: Empowering LLMs for Spatio-Temporal Reasoning in Time Series via Spatial-Aware Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/ni-2026-streasoner-empowering-llms-spatio-temporal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Juntong Ni, Shiyu Wang, Qi He, et al.*2026 · 3 citations*
57. **[K-Merge: Online Continual Merging of Adapters for On-device Large Language Models](https://md.research.elamur.ai/free/en/papers/shenaj-2026-k-merge-online-continual-merging/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Donald Shenaj, Ondrej Bohdal, Taha Ceritli, et al.*2026 · 2 citations*
58. **[CaTS-Bench: Can Language Models Describe Time Series?](https://md.research.elamur.ai/free/en/papers/zhou-2026-cats-bench-can-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Luca Zhou, Pratham Yashwante, Marshall Fisher, et al.*2026 · 1 citation*
59. **[Revisiting Metric Reliability for Fine-grained Evaluation of Machine Translation and Summarization in Indian Languages](https://md.research.elamur.ai/free/en/papers/yari-2026-revisiting-metric-reliability-fine-grained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Amir Hossein Yari, Kalmit Kulkarni, Ahmad Raza Khan, et al.*2026 · 1 citation*
60. **[SynthLLM: An LLM-based Scalable Synthetic Data Generation Pipeline for Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/panahi-2026-synthllm-llm-based-scalable-synthetic/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Solmaz Panahi, Vasudevan Nedumpozhimana, John Kelleher*2026 · 1 citation*
61. **[Bangla Key2Text: Text Generation from Keywords for a Low Resource Language](https://md.research.elamur.ai/free/en/papers/talukder-2026-bangla-key2text-text-generation-keywords/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Tonmoy Talukder, G M Shahariar*2026*
62. **[Comparing Approaches to Automatic Summarization in Less-Resourced Languages](https://md.research.elamur.ai/free/en/papers/michel-2026-comparing-approaches-automatic-summarization-less/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Chester Palen-Michel, Constantine Lignos*2026*
63. **[Enhancing Zero-Shot Time Series Forecasting in Off-the-Shelf LLMs via Noise Injection Prompting](https://md.research.elamur.ai/free/en/papers/yin-2026-enhancing-zero-shot-time-series/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xingyou Yin, Ceyao Zhang, Min Hu, et al.*2026*
64. **[Generation of Instruction and Preference Dataset for Improving Japanese Instruction Following in LLMs](https://md.research.elamur.ai/free/en/papers/moriyama-2026-generation-instruction-preference-dataset-improving/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kei Moriyama, Takashi Kodama, Kouta Nakayama*2026*
65. [**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/)
66. **[Language-Aware Token Boosting: LLM Language Confusion Reduction Without Tuning](https://md.research.elamur.ai/free/en/papers/ukarapol-2026-language-aware-token-boosting-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Trapoom Ukarapol, Pakhapoom Sarapat, Nut Chukamphaeng*2026*
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