---
title: "Who cites Tsendsuren Munkhdalai — 262 papers of our library"
description: "262 papers of the Elamur Research library cite the works of Tsendsuren Munkhdalai, found in their bibliographies; the most cited first."
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---
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# Who cites Tsendsuren Munkhdalai

269 citations of their works from 262 papers of our library (of the 149,439 whose bibliographies we read) · 47 with a page here, the most cited first · [← Tsendsuren Munkhdalai](https://md.research.elamur.ai/free/en/authors/tsendsuren-munkhdalai/)

1. **[Making Pre-trained Language Models Better Few-shot Learners](https://md.research.elamur.ai/free/en/papers/gao-2021-making-pre-trained-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Gao, Adam Fisch, Danqi Chen*2021 · 1,987 citations*
2. [**Multitask Prompted Training Enables Zero-Shot Task Generalization arXiv:2110.08207**Victor Sanh, Albert Webson, Colin Raffel, et al.*2021 · 1,612 citations*](https://md.research.elamur.ai/free/en/papers/sanh-2021-multitask-prompted-training-enables-zero/)
3. [**The Flan Collection: Designing Data and Methods for Effective Instruction Tuning arXiv:2301.13688**Shayne Longpre, Le Hou, Tu Vu, et al.*2023 · 607 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2023-flan-collection-designing-data-methods/)
4. [**Editing Models with Task Arithmetic arXiv:2212.04089**Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.*2022 · 402 citations*](https://md.research.elamur.ai/free/en/papers/ilharco-2022-editing-models-task-arithmetic/)
5. **[A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios](https://md.research.elamur.ai/free/en/papers/hedderich-2021-survey-recent-approaches-natural-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Michael A. Hedderich, Lukas Lange, Heike Adel, et al.*2021 · 401 citations*
6. **[SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer](https://md.research.elamur.ai/free/en/papers/vu-2022-spot-better-frozen-model-adaptation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tu Vu, Brian Lester, Noah Constant, et al.*2022 · 306 citations*
7. **[Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks](https://md.research.elamur.ai/free/en/papers/mahabadi-2021-parameter-efficient-multi-task-fine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rabeeh Karimi Mahabadi, Sebastian Ruder, Mostafa Dehghani, et al.*2021 · 258 citations*
8. [**OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization arXiv:2212.12017**Srinivasan Iyer, Xi Victoria Lin, Ramakanth Pasunuru, et al.*2022 · 244 citations*](https://md.research.elamur.ai/free/en/papers/iyer-2022-opt-iml-scaling-language-model/)
9. **[EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing](https://md.research.elamur.ai/free/en/papers/dong-2019-editnts-neural-programmer-interpreter-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yue Dong, Zichao Li, Mehdi Rezagholizadeh, et al.*2019 · 244 citations*
10. **[Noisy Channel Language Model Prompting for Few-Shot Text Classification](https://md.research.elamur.ai/free/en/papers/min-2021-noisy-channel-language-model-prompting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sewon Min, Mike Lewis, Hannaneh Hajishirzi, et al.*2021 · 243 citations*
11. **[Data-Driven Sentence Simplification: Survey and Benchmark](https://md.research.elamur.ai/free/en/papers/manchego-2020-data-driven-sentence-simplification-survey/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Fernando Alva-Manchego, Carolina Scarton, Lucia Specia*2020 · 213 citations*
12. **[CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP](https://md.research.elamur.ai/free/en/papers/ye-2021-crossfit-few-shot-learning-challenge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qinyuan Ye, Bill Yuchen Lin, Xiang Ren*2021 · 210 citations*
13. **[Merging Models with Fisher-Weighted Averaging](https://md.research.elamur.ai/free/en/papers/matena-2021-merging-models-fisher-weighted-averaging/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Michael Matena, Colin Raffel*2021 · 208 citations*
14. **[MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention](https://md.research.elamur.ai/free/en/papers/jiang-2024-minference-1-0-accelerating-pre/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Huiqiang Jiang, Yucheng Li, Chengruidong Zhang, et al.*2024 · 202 citations*
15. [**Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier arXiv:2412.04261**John Dang, Shivalika Singh, Daniel D'souza, et al.*2024 · 184 citations*](https://md.research.elamur.ai/free/en/papers/dang-2024-aya-expanse-combining-research-breakthroughs/)
16. **[Controllable Text Simplification with Explicit Paraphrasing](https://md.research.elamur.ai/free/en/papers/maddela-2021-controllable-text-simplification-explicit-paraphrasing/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Mounica Maddela, Fernando Alva-Manchego, Wei Xu*2021 · 164 citations*
17. **[The (Un)Suitability of Automatic Evaluation Metrics for Text Simplification](https://md.research.elamur.ai/free/en/papers/manchego-2021-un-suitability-automatic-evaluation-metrics/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Fernando Alva-Manchego, Carolina Scarton, Lucia Specia*2021 · 156 citations*
18. **[What to Pre-Train on? Efficient Intermediate Task Selection](https://md.research.elamur.ai/free/en/papers/poth-2021-what-pre-train-efficient-intermediate/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Clifton Poth, Jonas Pfeiffer, Andreas Rücklé, et al.*2021 · 132 citations*
19. **[InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory](https://md.research.elamur.ai/free/en/papers/xiao-2024-infllm-training-free-long-context/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chaojun Xiao, Pengle Zhang, Xu Han, et al.*2024 · 126 citations*
20. **[ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts](https://md.research.elamur.ai/free/en/papers/asai-2022-attempt-parameter-efficient-multi-task/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Akari Asai, Mohammadreza Salehi, Matthew Peters, et al.*2022 · 122 citations*
21. [**ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning arXiv:2111.10952**Vamsi Aribandi, Yi Tay, Tal Schuster, et al.*2021 · 114 citations*](https://md.research.elamur.ai/free/en/papers/aribandi-2021-ext5-towards-extreme-multi-task/)
22. **[Chain of Agents: Large Language Models Collaborating on Long-Context Tasks](https://md.research.elamur.ai/free/en/papers/zhang-2024-chain-agents-large-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yusen Zhang, Ruoxi Sun, Yanfei Chen, et al.*2024 · 104 citations*
23. [**Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities arXiv:2408.07666**Enneng Yang, Li Shen, Guibing Guo, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-model-merging-llms-mllms-methods/)
24. **[English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too](https://md.research.elamur.ai/free/en/papers/phang-2020-english-intermediate-task-training-improves/) [Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL)](https://md.research.elamur.ai/free/en/venues/aacl/)**Jason Phang, Iacer Calixto, Phu Mon Htut, et al.*2020 · 70 citations*
25. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
26. [**Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling arXiv:2406.07522**Liliang Ren, Yang Liu, Yadong Lu, et al.*2024 · 59 citations*](https://md.research.elamur.ai/free/en/papers/ren-2024-samba-simple-hybrid-state-space/)
27. [**Kimi Linear: An Expressive, Efficient Attention Architecture arXiv:2510.26692**Kimi Team, Yu Zhang, Zongyu Lin, et al.*2025 · 51 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-linear-expressive-efficient/)
28. **[The SAMER Arabic Text Simplification Corpus](https://md.research.elamur.ai/free/en/papers/alhafni-2024-samer-arabic-text-simplification-corpus/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Bashar Alhafni, Reem Hazim, Juan David Pineros Liberato, et al.*2024 · 30 citations*
29. **[Distilling an End-to-End Voice Assistant Without Instruction Training Data](https://md.research.elamur.ai/free/en/papers/held-2025-distilling-end-end-voice-assistant/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**William Held, Yanzhe Zhang, Minzhi Li, et al.*2025 · 18 citations*
30. [**Linearizing Large Language Models arXiv:2405.06640**Jean Mercat, Igor Vasiljevic, Sedrick Keh, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/mercat-2024-linearizing-large-language-models/)
31. [**A Survey on Latent Reasoning arXiv:2507.06203**Rui-Jie Zhu, Tianhao Peng, Tianhao Cheng, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-survey-latent-reasoning/)
32. **[Self-supervised Speech Representations Still Struggle with African American Vernacular English](https://md.research.elamur.ai/free/en/papers/chang-2024-self-supervised-speech-representations-still/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Kalvin Chang, Yi-Hui Chou, Jiatong Shi, et al.*2024 · 10 citations*
33. **[Nature-Inspired Population-Based Evolution of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-nature-inspired-population-based-evolution/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiqun Zhang, Peng Ye, Xiaocui Yang, et al.*2026 · 8 citations*
34. **[Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide](https://md.research.elamur.ai/free/en/papers/szep-2026-fine-tuning-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Marton Szep, Daniel Rueckert, Rüdiger von Eisenhart-Rothe, et al.*2026 · 7 citations*
35. **[CAFE: Retrieval Head-based Coarse-to-Fine Information Seeking to Enhance Multi-Document QA Capability](https://md.research.elamur.ai/free/en/papers/peng-2025-cafe-retrieval-head-based-coarse/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Han Peng, Jinhao Jiang, Zican Dong, et al.*2025 · 4 citations*
36. **[When More Thinking Hurts: Overthinking in LLM Test-Time Compute Scaling](https://md.research.elamur.ai/free/en/papers/zhou-2026-when-more-thinking-hurts-overthinking/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shu Zhou, Rui Ling, Junan Chen, et al.*2026 · 2 citations*
37. **[Why Do More Experts Fail? A Theoretical Analysis of Model Merging](https://md.research.elamur.ai/free/en/papers/wang-2026-why-do-more-experts-fail/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zijing Wang, Xingle Xu, YongKang Liu, et al.*2026 · 2 citations*
38. [**Family Matters: Language Transfer and Merging for Adapting Small LLMs to Faroese arXiv:2510.00810**Jenny Kunz, Iben Nyholm Debess, Annika Simonsen*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/kunz-2025-family-matters-language-transfer-merging/)
39. **[When Do Large Language Models Exhibit Unsolicited Deception?](https://md.research.elamur.ai/free/en/papers/taylor-2026-when-do-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Samuel M. Taylor, Benjamin K. Bergen*2026 · 1 citation*
40. **[An Empirical Analysis of Task Relations in the Multi-Task Annotation of an Arabizi Corpus](https://md.research.elamur.ai/free/en/papers/gugliotta-2023-empirical-analysis-task-relations-multi/) [Conference on Language, Data and Knowledge](https://md.research.elamur.ai/free/en/venues/ldk/)**Elisa Gugliotta, Marco Dinarelli*2023 · 1 citation*
41. **[CoMeT: Collaborative Memory Transformer for Efficient Long Context Modeling](https://md.research.elamur.ai/free/en/papers/zhao-2026-comet-collaborative-memory-transformer-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Runsong Zhao, Shilei Liu, Jiwei Tang, et al.*2026*
42. **[DivMerge: A divergence-based model merging method for multi-tasking](https://md.research.elamur.ai/free/en/papers/touayouch-2026-divmerge-divergence-based-model-merging/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Brahim Touayouch, Loïc Fosse, Géraldine Damnati, et al.*2026*
43. **[Merging Continual Pretraining Models for Domain-Specialized LLMs: A Case Study in Finance](https://md.research.elamur.ai/free/en/papers/ueda-2026-merging-continual-pretraining-models-domain/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kentaro Ueda, François Portet, Hirohiko Suwa, et al.*2026*
44. **[Opportunities and Challenges of LLMs in Education: An NLP Perspective](https://md.research.elamur.ai/free/en/papers/vajjala-2026-opportunities-challenges-llms-education-nlp/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Sowmya Vajjala, Bashar Alhafni, Stefano Banno, et al.*2026*
45. **[Simplify-Pro: A Two-level and Progressive LLM-based Framework for Auto Long Text Simplification](https://md.research.elamur.ai/free/en/papers/zhou-2026-simplify-pro-two-level-progressive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Peng Zhou, Guangxin Li, Xiaoying Huang, et al.*2026*
46. **[Tree-Notebook: A Context-Aware Agent with Tree Search and Entropy-Aware Data Shadow for Interactive Data Science](https://md.research.elamur.ai/free/en/papers/qiu-2026-tree-notebook-context-aware-agent/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junkun Qiu, Min Huang, Qinghai Miao*2026*
47. **[Will it Merge? On The Causes of Model Mergeability](https://md.research.elamur.ai/free/en/papers/rahamim-2026-will-it-merge-causes-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Adir Rahamim, Asaf Yehudai, Boaz Carmeli, et al.*2026*

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