---
title: "Who cites Premise Order Matters in — 55 citing papers"
description: "55 papers of the Elamur Research library cite «Premise Order Matters in Reasoning with Large Language Models», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/chen-2024-premise-order-matters-reasoning-large/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/chen-2024-premise-order-matters-reasoning-large/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Premise Order Matters in Reasoning with Large…](https://md.research.elamur.ai/free/en/papers/chen-2024-premise-order-matters-reasoning-large/) / cited by

# Who cites «Premise Order Matters in Reasoning with Large Language Models»

55 papers of our library cite it (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · [← back to «Premise Order Matters in Reasoning with Large Language Models»](https://md.research.elamur.ai/free/en/papers/chen-2024-premise-order-matters-reasoning-large/)

1. **[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*
2. [**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/)
3. **[On Memorization of Large Language Models in Logical Reasoning](https://md.research.elamur.ai/free/en/papers/xie-2025-memorization-large-language-models-logical/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Chulin Xie, Yangsibo Huang, Chiyuan Zhang, et al.*2025 · 45 citations*
4. **[LLM The Genius Paradox: A Linguistic and Math Expert's Struggle with Simple Word-based Counting Problems](https://md.research.elamur.ai/free/en/papers/xu-2025-llm-genius-paradox-linguistic-math/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nan Xu, Xuezhe Ma*2025 · 17 citations*
5. **[Quantifying the Impact of Structured Output Format on Large Language Models through Causal Inference](https://md.research.elamur.ai/free/en/papers/yuan-2026-quantifying-impact-structured-output-format/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Han Yuan, Yue Zhao, Li Zhang, et al.*2026 · 2 citations*
6. **[When LLMs Annotate: Reliability Challenges in Low-Resource NLI](https://md.research.elamur.ai/free/en/papers/panahi-2026-when-llms-annotate-reliability-challenges/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Solmaz Panahi, John Kelleher, Vasudevan Nedumpozhimana*2026 · 1 citation*
7. **[Did You Forget What I Asked? Prospective Memory Failures in Large Language Models](https://md.research.elamur.ai/free/en/papers/mittal-2026-did-you-forget-what-i/) [Workshop on Trustworthy NLP](https://md.research.elamur.ai/free/en/venues/trustnlp/)**Avni Mittal*2026*
8. **[GSM-Noise: Exploring and Enhancing Large Language Models' Reasoning under Noisy Inputs](https://md.research.elamur.ai/free/en/papers/zhang-2026-gsm-noise-exploring-enhancing-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhengxin Zhang, Chengyu Huang, Xufu Liu, et al.*2026*
9. **[Reliable Use of Lemmas via Eligibility Reasoning and Section-Aware Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/xu-2026-reliable-use-lemmas-eligibility-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhikun Xu, Xiaodong Yu, Ben Zhou, et al.*2026*
10. **[Tracing the Light of Thought: A Probabilistic Self- and Cross-Consistency Verification Mechanism Improving Mathematical Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/liu-2026-tracing-light-thought-probabilistic-self/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaoyang Liu, Dawei Wang, Tian Li, et al.*2026*
11. **[Vertical Routing: A Cost-Efficient Collaboration Routing Framework](https://md.research.elamur.ai/free/en/papers/shen-2026-vertical-routing-cost-efficient-collaboration/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Si Shen, Peijun Shen, Danhao Zhu*2026*

44 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/chen-2024-premise-order-matters-reasoning-large/) — Premise Order Matters in Reasoning with Large Language Models
