---
title: "Who cites Di Liu — 255 papers of our library — Elamur Research"
description: "255 papers of the Elamur Research library cite the works of Di Liu, found in their bibliographies; the most cited first."
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---
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# Who cites Di Liu

255 citations of their works from 255 papers of our library (of the 149,439 whose bibliographies we read) · 55 with a page here, the most cited first · [← Di Liu](https://md.research.elamur.ai/free/en/authors/di-liu/)

1. [**WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct arXiv:2308.09583**Haipeng Luo, Qingfeng Sun, Can Xu, et al.*2023 · 372 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-wizardmath-empowering-mathematical-reasoning-large/)
2. [**Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning arXiv:2503.09516**Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.*2025 · 322 citations*](https://md.research.elamur.ai/free/en/papers/jin-2025-search-r1-training-llms-reason/)
3. **[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*
4. **[GSM-Plus: A Comprehensive Benchmark for Evaluating the Robustness of LLMs as Mathematical Problem Solvers](https://md.research.elamur.ai/free/en/papers/li-2024-gsm-plus-comprehensive-benchmark-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qintong Li, Leyang Cui, Xueliang Zhao, et al.*2024 · 108 citations*
5. **[Multi-Step Reasoning with Large Language Models, a Survey](https://md.research.elamur.ai/free/en/papers/plaat-2024-multi-step-reasoning-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Aske Plaat, Annie Wong, Suzan Verberne, et al.*2024 · 106 citations*
6. **[MoBA: Mixture of Block Attention for Long-Context LLMs](https://md.research.elamur.ai/free/en/papers/lu-2025-moba-mixture-block-attention/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Enzhe Lu, Zhejun Jiang, Jingyuan Liu, et al.*2025 · 80 citations*
7. [**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/)
8. **[A Peek into Token Bias: Large Language Models Are Not Yet Genuine Reasoners](https://md.research.elamur.ai/free/en/papers/jiang-2024-peek-into-token-bias-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bowen Jiang, Yangxinyu Xie, Zhuoqun Hao, et al.*2024 · 64 citations*
9. [**A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond arXiv:2503.21614**Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.*2025 · 55 citations*](https://md.research.elamur.ai/free/en/papers/qu-2025-survey-efficient-reasoning-large-reasoning/)
10. [**Beyond Accuracy: Evaluating the Reasoning Behavior of Large Language Models — A Survey arXiv:2404.01869**Philipp Mondorf, Barbara Plank*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/mondorf-2024-accuracy-evaluating-reasoning-behavior-large/)
11. [**Q*: Improving Multi-step Reasoning for LLMs with Deliberative Planning arXiv:2406.14283**Chaojie Wang, Yanchen Deng, Zhiyi Lyu, et al.*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-q-improving-multi-step-reasoning/)
12. **[Reasoning Aware Self-Consistency: Leveraging Reasoning Paths for Efficient LLM Sampling](https://md.research.elamur.ai/free/en/papers/wan-2025-reasoning-aware-self-consistency-leveraging/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Guangya Wan, Yuqi Wu, Jie Chen, et al.*2025 · 29 citations*
13. **[ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection](https://md.research.elamur.ai/free/en/papers/yan-2026-errorradar-benchmarking-complex-mathematical-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Yan, Shen Wang, Jiahao Huo, et al.*2026 · 23 citations*
14. **[CoMAT: Chain of Mathematically Annotated Thought Improves Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/leang-2025-comat-chain-mathematically-annotated-thought/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Joshua Ong Jun Leang, Aryo Pradipta Gema, Shay B. Cohen*2025 · 14 citations*
15. [**U-MATH: A University-Level Benchmark for Evaluating Mathematical Skills in LLMs arXiv:2412.03205**Konstantin Chernyshev, Vitaliy Polshkov, Ekaterina Artemova, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/chernyshev-2024-u-math-university-level-benchmark/)
16. **[Learning from Diverse Reasoning Paths with Routing and Collaboration](https://md.research.elamur.ai/free/en/papers/lei-2025-learning-diverse-reasoning-paths-routing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhenyu Lei, Zhen Tan, Song Wang, et al.*2025 · 11 citations*
17. **[ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning](https://md.research.elamur.ai/free/en/papers/sun-2025-reasonmed-370k-multi-agent-generated/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yu Sun, Xingyu Qian, Weiwen Xu, et al.*2025 · 11 citations*
18. **[A Survey of Inductive Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2026-survey-inductive-reasoning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kedi Chen, Dezhao Ruan, Yuhao Dan, et al.*2026 · 10 citations*
19. [**Implicit Reasoning in Large Language Models: A Comprehensive Survey arXiv:2509.02350**Jindong Li, Yali Fu, Li Fan, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-implicit-reasoning-large-language-models/)
20. **[MathFusion: Enhancing Mathematical Problem-solving of LLM through Instruction Fusion](https://md.research.elamur.ai/free/en/papers/pei-2025-mathfusion-enhancing-mathematical-problem-solving/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qizhi Pei, Lijun Wu, Zhuoshi Pan, et al.*2025 · 10 citations*
21. **[Planning with Multi-Constraints via Collaborative Language Agents](https://md.research.elamur.ai/free/en/papers/zhang-2025-planning-multi-constraints-collaborative-language/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Cong Zhang, Xin Deik Goh, Dexun Li, et al.*2025 · 10 citations*
22. **[Position: LLMs Can be Good Tutors in English Education](https://md.research.elamur.ai/free/en/papers/ye-2025-position-llms-can-be-good/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jingheng Ye, Shen Wang, Deqing Zou, et al.*2025 · 9 citations*
23. **[Assessing the Creativity of LLMs in Proposing Novel Solutions to Mathematical Problems](https://md.research.elamur.ai/free/en/papers/ye-2024-assessing-creativity-llms-proposing-novel/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Junyi Ye, Jingyi Gu, Xinyun Zhao, et al.*2024 · 8 citations*
24. **[TSPO: Breaking the Double Homogenization Dilemma in Multi-turn Search Policy Optimization](https://md.research.elamur.ai/free/en/papers/ma-2026-tspo-breaking-double-homogenization-dilemma/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shichao Ma, Zhiyuan Ma, Ming Yang, et al.*2026 · 7 citations*
25. **[Math Neurosurgery: Isolating Language Models' Math Reasoning Abilities Using Only Forward Passes](https://md.research.elamur.ai/free/en/papers/christ-2025-math-neurosurgery-isolating-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bryan R Christ, Zachary Gottesman, Jonathan Kropko, et al.*2025 · 7 citations*
26. [**Cutting Through the Noise: Boosting LLM Performance on Math Word Problems**Ujjwala Anantheswaran, Himanshu Gupta, Kevin Scaria, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/anantheswaran-2024-cutting-through-noise-boosting-llm/)
27. **[Scaling Behaviors of LLM Reinforcement Learning Post-Training: An Empirical Study in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/tan-2026-scaling-behaviors-llm-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zelin Tan, Hejia Geng, Xiaohang Yu, et al.*2026 · 6 citations*
28. [**From Blind Solvers to Logical Thinkers: Benchmarking LLMs' Logical Integrity on Faulty Mathematical Problems arXiv:2410.18921**A M Muntasir Rahman, Junyi Ye, Wei Yao, et al.*2024 · 6 citations*](https://md.research.elamur.ai/free/en/papers/rahman-2024-blind-solvers-logical-thinkers-benchmarking/)
29. [**Give me a hint: Can LLMs take a hint to solve math problems? arXiv:2410.05915**Vansh Agrawal, Pratham Singla, Amitoj Singh Miglani, et al.*2024 · 6 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2024-give-me-hint-llms-take/)
30. **[Evaluating Numeracy of Language Models as a Natural Language Inference Task](https://md.research.elamur.ai/free/en/papers/mahendra-2025-evaluating-numeracy-language-models-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rahmad Mahendra, Damiano Spina, Lawrence Cavedon, et al.*2025 · 4 citations*
31. **[MathMist: A Parallel Multilingual Benchmark Dataset for Mathematical Problem Solving and Reasoning](https://md.research.elamur.ai/free/en/papers/sobhani-2026-mathmist-parallel-multilingual-benchmark-dataset/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mahbub E Sobhani, Md. Faiyaz Abdullah Sayeedi, Tasnim Mohiuddin, et al.*2026 · 3 citations*
32. **[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*
33. **[GM-PRM: A Generative Multimodal Process Reward Model for Multimodal Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2026-gm-prm-generative-multimodal-process/) [Workshop on Advances in Language and Vision Research (ALVR)](https://md.research.elamur.ai/free/en/venues/alvr/)**Jianghangfan Zhang, Yibo Yan, Kening Zheng, et al.*2026 · 2 citations*
34. **[A Survey of Deep Learning for Geometry Problem Solving](https://md.research.elamur.ai/free/en/papers/ma-2026-survey-deep-learning-geometry-problem/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianzhe Ma, Wenxuan Wang, Qin Jin*2026 · 1 citation*
35. **[Bridging the Culture Gap: A Framework for LLM-Driven Socio-Cultural Localization of Math Word Problems in Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/azime-2026-bridging-culture-gap-framework-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Israel Abebe Azime, Tadesse Destaw Belay, Dietrich Klakow, et al.*2026 · 1 citation*
36. **[CuMA: Aligning LLMs with Sparse Cultural Values via Demographic-Aware Mixture of Adapters](https://md.research.elamur.ai/free/en/papers/sun-2026-cuma-aligning-llms-sparse-cultural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ao Sun, Xiaoyu Wang, Zhe Tan, et al.*2026 · 1 citation*
37. **[DELTA: Dynamic Layer-Aware Token Attention for Efficient Long-Context Reasoning](https://md.research.elamur.ai/free/en/papers/zarch-2026-delta-dynamic-layer-aware-token/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hossein Entezari Zarch, Lei Gao, Chaoyi Jiang, et al.*2026 · 1 citation*
38. **[Reasoning Fails Where Step Flow Breaks](https://md.research.elamur.ai/free/en/papers/xu-2026-reasoning-fails-where-step-flow/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyu Xu, Yulan Pan, Xiaosong Yuan, et al.*2026 · 1 citation*
39. **[RISER: Orchestrating Latent Reasoning Skills for Adaptive Activation Steering](https://md.research.elamur.ai/free/en/papers/ye-2026-riser-orchestrating-latent-reasoning-skills/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wencheng Ye, Xiaoyang Yuan, Yi Bin, et al.*2026 · 1 citation*
40. **[A Survey of Multimodal Mathematical Reasoning: From Perception, Alignment to Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2026-survey-multimodal-mathematical-reasoning-perception/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Yang, Sihong Wu, Yilun Zhao, et al.*2026*
41. **[Bayesian Social Deduction with Graph-Informed Language Models](https://md.research.elamur.ai/free/en/papers/rahimirad-2026-bayesian-social-deduction-graph-informed/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shahab Rahimirad, Guven Gergerli, Lucia Romero, et al.*2026*
42. **[Consistency of LLMs to Comparative Statements in Mathematical Reasoning Tasks](https://md.research.elamur.ai/free/en/papers/san-2026-consistency-llms-comparative-statements-mathematical/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aidan W. San, Daniel Juyoung Son, Xiaodong Liu, et al.*2026*
43. **[C³D: Enhancing LLM Reasoning via Confidence-Guided Contrastive Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2026-c-3-d-enhancing-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yufeng Zhang, Xuepeng Wang, Lingxiang Wu, et al.*2026*
44. **[Exploring Fine-Tuning for In-Context Retrieval and Efficient KV-Caching in Long-Context Language Models](https://md.research.elamur.ai/free/en/papers/molfese-2026-exploring-fine-tuning-context-retrieval/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Francesco Maria Molfese, Momchil Hardalov, Rexhina Blloshmi, et al.*2026*
45. **[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*
46. **[Learning from Mistakes: Negative Reasoning Samples Enhance Out-of-Domain Generalization](https://md.research.elamur.ai/free/en/papers/xueyun-2026-learning-mistakes-negative-reasoning-samples/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tian Xueyun, MingHua Ma, Bingbing Xu, et al.*2026*
47. **[LEDGER: Scaling Agentic Document Editing with Dependency-aware Graph Retrieval](https://md.research.elamur.ai/free/en/papers/wang-2026-ledger-scaling-agentic-document-editing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hang Wang, Utkarsh Garg, Reza Davari, et al.*2026*
48. **[Linear Probes Detect Task Format, Not Reasoning Mode in Language Model Hidden States](https://md.research.elamur.ai/free/en/papers/sahoo-2026-linear-probes-detect-task-format/) [Workshop on Trustworthy NLP](https://md.research.elamur.ai/free/en/venues/trustnlp/)**Subramanyam Sahoo, Vinija Jain, Aman Chadha, et al.*2026*
49. **[On LLM Prompting Techniques for Arabic Language Arithmetic Reasoning](https://md.research.elamur.ai/free/en/papers/alenezi-2026-llm-prompting-techniques-arabic-language/) [Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks](https://md.research.elamur.ai/free/en/venues/osact/)**Reem Alenezi, Ayed Atallah Salman*2026*
50. **[On Temperature-Constrained Non-Deterministic Machine Translation: Potential and Evaluation](https://md.research.elamur.ai/free/en/papers/wang-2026-temperature-constrained-non-deterministic-machine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weichuan Wang, Mingyang Liu, Chen Ma, et al.*2026*
51. **[QueueEDIT: Structural Self-Correction for Sequential Model Editing in LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-queueedit-structural-self-correction-sequential/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Taolin Zhang, Haidong Kang, Dongyang Li, et al.*2026*
52. **[RADAR: A Reasoning-Guided Attribution Framework for Explainable Visual Data Analysis](https://md.research.elamur.ai/free/en/papers/rani-2026-radar-reasoning-guided-attribution-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Anku Rani, Aparna Garimella, Apoorv Saxena, et al.*2026*
53. **[ReActR: Reasoning through Error-Activated Reflection for LLM Post-Training](https://md.research.elamur.ai/free/en/papers/sun-2026-reactr-reasoning-through-error-activated/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lina Sun*2026*
54. **[Tailoring Diagnostic Modeling to Individual Learners: Personalized Distractor Generation via MCTS-Guided Reasoning Reconstruction](https://md.research.elamur.ai/free/en/papers/wu-2026-tailoring-diagnostic-modeling-individual-learners/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tao Wu, Jingyuan Chen, Wang Lin, et al.*2026*
55. **[Why do Large Language Models Fail in Low-resource Translation? Unraveling the Token Dynamics of Large Language Models for Machine Translation](https://md.research.elamur.ai/free/en/papers/qian-2026-why-do-large-language-models/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Shenbin Qian, Yves Scherrer*2026*

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