---
title: "Who cites Dimitris Papailiopoulos — 143 papers of our library"
description: "143 papers of the Elamur Research library cite the works of Dimitris Papailiopoulos, found in their bibliographies; the most cited first."
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---
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# Who cites Dimitris Papailiopoulos

143 citations of their works from 143 papers of our library (of the 149,439 whose bibliographies we read) · 51 with a page here, the most cited first · [← Dimitris Papailiopoulos](https://md.research.elamur.ai/free/en/authors/dimitris-papailiopoulos/)

1. [**Unleashing the potential of prompt engineering for large language models arXiv:2310.14735 · Patterns 6(6) 101,260 (2025)**Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.*2023 · 536 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-unleashing-potential-prompt-engineering-large/)
2. [**Jamba: A Hybrid Transformer-Mamba Language Model arXiv:2403.19887**Opher Lieber, Barak Lenz, Hofit Bata, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/lieber-2024-jamba-hybrid-transformer-mamba-language/)
3. [**OpenThoughts: Data Recipes for Reasoning Models arXiv:2506.04178**Etash Guha, Ryan Marten, Sedrick Keh, et al.*2025 · 122 citations*](https://md.research.elamur.ai/free/en/papers/guha-2025-openthoughts-data-recipes-reasoning-models/)
4. [**CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution arXiv:2401.03065**Alex Gu, Baptiste Rozière, Hugh Leather, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-cruxeval-benchmark-code-reasoning-understanding/)
5. [**A Survey on Efficient Inference for Large Language Models arXiv:2404.14294**Zixuan Zhou, Xuefei Ning, Ke Hong, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-survey-efficient-inference-large-language/)
6. **[MathArena: Evaluating LLMs on Uncontaminated Math Competitions](https://md.research.elamur.ai/free/en/papers/balunovic-2025-matharena-evaluating-llms-uncontaminated-math/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Mislav Balunović, Jasper Dekoninck, Ivo Petrov, et al.*2025 · 99 citations*
7. [**An Empirical Study of Mamba-based Language Models arXiv:2406.07887**Roger Waleffe, Wonmin Byeon, Duncan Riach, et al.*2024 · 67 citations*](https://md.research.elamur.ai/free/en/papers/waleffe-2024-empirical-study-mamba-based-language/)
8. [**What Algorithms can Transformers Learn? A Study in Length Generalization arXiv:2310.16028**Hattie Zhou, Arwen Bradley, Etai Littwin, et al.*2023 · 67 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-algorithms-transformers-learn-study-length/)
9. [**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/)
10. [**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/)
11. [**Premise Order Matters in Reasoning with Large Language Models arXiv:2402.08939**Xinyun Chen, Ryan A. Chi, Xuezhi Wang, et al.*2024 · 58 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-premise-order-matters-reasoning-large/)
12. [**Repeat After Me: Transformers are Better than State Space Models at Copying arXiv:2402.01032**Samy Jelassi, David Brandfonbrener, Sham M. Kakade, et al.*2024 · 57 citations*](https://md.research.elamur.ai/free/en/papers/jelassi-2024-repeat-after-me-transformers-better/)
13. [**Tokenization counts: the impact of tokenization on arithmetic in frontier LLMs arXiv:2402.14903**Aaditya K. Singh, DJ Strouse*2024 · 55 citations*](https://md.research.elamur.ai/free/en/papers/singh-2024-tokenization-counts-impact-tokenization-arithmetic/)
14. [**Hymba: A Hybrid-head Architecture for Small Language Models arXiv:2411.13676**Xin Dong, Yonggan Fu, Shizhe Diao, et al.*2024 · 50 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-hymba-hybrid-head-architecture-small/)
15. [**Zamba: A Compact 7B SSM Hybrid Model arXiv:2405.16712**Paolo Glorioso, Quentin Anthony, Yury Tokpanov, et al.*2024 · 50 citations*](https://md.research.elamur.ai/free/en/papers/glorioso-2024-zamba-compact-7b-ssm-hybrid/)
16. [**Reasoning with Latent Thoughts: On the Power of Looped Transformers arXiv:2502.17416**Nikunj Saunshi, Nishanth Dikkala, Zhiyuan Li, et al.*2025 · 44 citations*](https://md.research.elamur.ai/free/en/papers/saunshi-2025-reasoning-latent-thoughts-power-looped/)
17. [**The pitfalls of next-token prediction arXiv:2403.06963**Gregor Bachmann, Vaishnavh Nagarajan*2024 · 39 citations*](https://md.research.elamur.ai/free/en/papers/bachmann-2024-pitfalls-next-token-prediction/)
18. **[Transformers Can Do Arithmetic with the Right Embeddings](https://md.research.elamur.ai/free/en/papers/mcleish-2024-transformers-arithmetic-right-embeddings/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Sean McLeish, Arpit Bansal, Alex Stein, et al.*2024 · 36 citations*
19. **[The Hidden Attention of Mamba Models](https://md.research.elamur.ai/free/en/papers/ali-2025-hidden-attention-mamba-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ameen Ali Ali, Itamar Zimerman, Lior Wolf*2025 · 32 citations*
20. [**Positional Description Matters for Transformers Arithmetic arXiv:2311.14737**Ruoqi Shen, Sébastien Bubeck, Ronen Eldan, et al.*2023 · 30 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-positional-description-matters-transformers-arithmetic/)
21. [**Transformers Can Achieve Length Generalization But Not Robustly arXiv:2402.09371**Yongchao Zhou, Uri Alon, Xinyun Chen, et al.*2024 · 29 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-transformers-achieve-length-generalization-but/)
22. **[NumeroLogic: Number Encoding for Enhanced LLMs' Numerical Reasoning](https://md.research.elamur.ai/free/en/papers/schwartz-2024-numerologic-number-encoding-enhanced-llms/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Eli Schwartz, Leshem Choshen, Joseph Shtok, et al.*2024 · 26 citations*
23. **[AICD Bench: A Challenging Benchmark for AI-Generated Code Detection](https://md.research.elamur.ai/free/en/papers/orel-2026-aicd-bench-challenging-benchmark-ai/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Daniil Orel, Dilshod Azizov, Indraneil Paul, et al.*2026 · 23 citations*
24. **[Understanding Transformer Reasoning Capabilities via Graph Algorithms](https://md.research.elamur.ai/free/en/papers/sanford-2024-understanding-transformer-reasoning-capabilities-graph/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Clayton Sanford, Bahare Fatemi, Ethan Hall, et al.*2024 · 21 citations*
25. [**RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval arXiv:2402.18510**Kaiyue Wen, Xingyu Dang, Kaifeng Lyu*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/wen-2024-rnns-transformers-yet-key-bottleneck/)
26. [**Looped Transformers for Length Generalization arXiv:2409.15647**Ying Fan, Yilun Du, Kannan Ramchandran, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/fan-2024-looped-transformers-length-generalization/)
27. **[Causal Language Modeling Can Elicit Search and Reasoning Capabilities on Logic Puzzles](https://md.research.elamur.ai/free/en/papers/shah-2024-causal-language-modeling-elicit-search/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Kulin Shah, Nishanth Dikkala, Xin Wang, et al.*2024 · 12 citations*
28. **[Optimizing Length Compression in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/cheng-2026-optimizing-length-compression-large-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengxiang Cheng, Dongping Chen, Mingyang Fu, et al.*2026 · 11 citations*
29. [**Chain-of-Thought Reasoning is a Policy Improvement Operator arXiv:2309.08589**Hugh Zhang, David C. Parkes*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-chain-thought-reasoning-policy-improvement/)
30. **[AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time](https://md.research.elamur.ai/free/en/papers/zhang-2025-alphaone-reasoning-models-thinking-slow/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junyu Zhang, Runpei Dong, Han Wang, et al.*2025 · 10 citations*
31. **[rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset](https://md.research.elamur.ai/free/en/papers/liu-2025-rstar-coder-scaling-competitive/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yifei Liu, Li Lyna Zhang, Yi Zhu, et al.*2025 · 8 citations*
32. **[DEBATE, TRAIN, EVOLVE: Self-Evolution of Language Model Reasoning](https://md.research.elamur.ai/free/en/papers/srivastava-2025-debate-train-evolve-self-evolution/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gaurav Srivastava, Zhenyu Bi, Meng Lu, et al.*2025 · 7 citations*
33. [**rStar2-Agent: Agentic Reasoning Technical Report arXiv:2508.20722**Ning Shang, Yifei Liu, Yi Zhu, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/shang-2025-rstar2-agent-agentic-reasoning/)
34. [**Explicitly Encoding Structural Symmetry is Key to Length Generalization in Arithmetic Tasks arXiv:2406.01895**Mahdi Sabbaghi, George Pappas, Hamed Hassani, et al.*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/sabbaghi-2024-explicitly-encoding-structural-symmetry-key/)
35. **[Which Reasoning Trajectories Teach Students to Reason Better? A Simple Metric of Informative Alignment](https://md.research.elamur.ai/free/en/papers/yang-2026-which-reasoning-trajectories-teach-students/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuming Yang, Mingyoung Lai, Wanxu Zhao, et al.*2026 · 4 citations*
36. **[Barriers to Discrete Reasoning with Transformers: A Survey Across Depth, Exactness, and Bandwidth](https://md.research.elamur.ai/free/en/papers/yuan-2026-barriers-discrete-reasoning-transformers-survey/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Michelle Yuan, Weiyi Sun, Amir H. Rezaeian, et al.*2026 · 3 citations*
37. **[Do LLMs Overthink Basic Math Reasoning? Benchmarking the Accuracy-Efficiency Tradeoff in Language Models](https://md.research.elamur.ai/free/en/papers/srivastava-2026-do-llms-overthink-basic-math/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Gaurav Srivastava, Aafiya Shamshad Hussain, Sriram Srinivasan, et al.*2026 · 3 citations*
38. **[SynthRL: Scaling Visual Reasoning with Verifiable Data Synthesis](https://md.research.elamur.ai/free/en/papers/wu-2026-synthrl-scaling-visual-reasoning-verifiable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zijian Wu, Jinjie Ni, Xiangyan Liu, et al.*2026 · 3 citations*
39. **[Author-in-the-Loop Response Generation and Evaluation: Integrating Author Expertise and Intent in Responses to Peer Review](https://md.research.elamur.ai/free/en/papers/ruan-2026-author-loop-response-generation-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qian Ruan, Iryna Gurevych*2026 · 2 citations*
40. **[ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments](https://md.research.elamur.ai/free/en/papers/wang-2026-reasoningguard-safeguarding-large-reasoning-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuquan Wang, Mi Zhang, Yining Wang, et al.*2026 · 1 citation*
41. **[ReProbe: Efficient Test-Time Scaling of Multi-Step Reasoning by Probing Internal States of Large Language Models](https://md.research.elamur.ai/free/en/papers/ni-2026-reprobe-efficient-test-time-scaling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingwei Ni, Ekaterina Fadeeva, Tianyi Wu, et al.*2026 · 1 citation*
42. **[ThinkBrake: Efficient Reasoning via Log-Probability Margin Guided Decoding](https://md.research.elamur.ai/free/en/papers/song-2026-thinkbrake-efficient-reasoning-log-probability/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sangjun Song, Minjae Oh, Seungkyu Lee, et al.*2026 · 1 citation*
43. **[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*
44. **[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*
45. **[Distilling Long-CoT Reasoning through Collaborative Step-wise Multi-Teacher Decoding](https://md.research.elamur.ai/free/en/papers/yun-2026-distilling-long-cot-reasoning-through/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Taewon Yun, Jisu Shin, Jeonghwan Choi, et al.*2026*
46. **[ExStrucTiny: A Benchmark for Schema-Variable Structured Information Extraction from Document Images](https://md.research.elamur.ai/free/en/papers/sibue-2026-exstructiny-benchmark-schema-variable-structured/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mathieu Sibue, Andrés Muñoz Garza, Samuel Mensah, et al.*2026*
47. **[From Implicit to Explicit: Token-Efficient Logical Supervision for Mathematical Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-implicit-explicit-token-efficient-logical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shaojie Wang, Liang Zhang*2026*
48. **[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*
49. **[Task-Related In-Context Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-task-related-context-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenqiang Wang, Peng Chen, Yan Xiao, et al.*2026*
50. **[Understanding In-Context Learning Beyond Transformers: An Investigation of State Space and Hybrid Architectures](https://md.research.elamur.ai/free/en/papers/wang-2026-understanding-context-learning-beyond-transformers/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shenran Wang, Timothy Tin-Long Tse, Jian Zhu*2026*
51. **[XLSR-MamBo: Scaling the Hybrid Mamba-Attention Backbone for Audio Deepfake Detection](https://md.research.elamur.ai/free/en/papers/ng-2026-xlsr-mambo-scaling-hybrid-mamba/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kwok-Ho Ng, Tingting Song, Yongdong WU, et al.*2026*

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