--- title: "Who cites Rethinking the Bounds of LLM — 63 citing papers" description: "63 papers of the Elamur Research library cite «Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?», found in their…" canonical: "https://research.elamur.ai/free/en/papers/wang-2024-rethinking-bounds-llm-reasoning/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wang-2024-rethinking-bounds-llm-reasoning/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Rethinking the Bounds of LLM Reasoning: Are…](https://md.research.elamur.ai/free/en/papers/wang-2024-rethinking-bounds-llm-reasoning/) / cited by # Who cites «Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?» 63 papers of our library cite it (of the 149,439 whose bibliographies we read) · 15 with a page here, the most cited first · [← back to «Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?»](https://md.research.elamur.ai/free/en/papers/wang-2024-rethinking-bounds-llm-reasoning/) 1. **[When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs](https://md.research.elamur.ai/free/en/papers/kamoi-2024-when-can-llms-actually-correct/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.*2024 · 161 citations* 2. [**Mixture-of-Agents Enhances Large Language Model Capabilities arXiv:2406.04692**Junlin Wang, Jue Wang, Ben Athiwaratkun, et al.*2024 · 116 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-mixture-agents-enhances-large/) 3. [**Multi-Agent Collaboration Mechanisms: A Survey of LLMs arXiv:2501.06322**Khanh-Tung Tran, Dung Dao, Minh-Duong Nguyen, et al.*2025 · 95 citations*](https://md.research.elamur.ai/free/en/papers/tran-2025-multi-agent-collaboration-mechanisms/) 4. [**RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning arXiv:2504.20073**Zihan Wang, Kangrui Wang, Qineng Wang, et al.*2025 · 71 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-ragen-understanding-self-evolution-llm/) 5. [**Scaling Large Language Model-based Multi-Agent Collaboration arXiv:2406.07155**Chen Qian, Zihao Xie, YiFei Wang, et al.*2024 · 70 citations*](https://md.research.elamur.ai/free/en/papers/qian-2024-scaling-large-language-model/) 6. **[Many Heads Are Better Than One: Improved Scientific Idea Generation by A LLM-Based Multi-Agent System](https://md.research.elamur.ai/free/en/papers/su-2025-many-heads-are-better-than/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoyang Su, Renqi Chen, Shixiang Tang, et al.*2025 · 40 citations* 7. **[MemInsight: Autonomous Memory Augmentation for LLM Agents](https://md.research.elamur.ai/free/en/papers/salama-2025-meminsight-autonomous-memory-augmentation-llm/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rana Salama, Jason Cai, Michelle Yuan, et al.*2025 · 22 citations* 8. **[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* 9. **[SILO-BENCH: A Scalable Environment for Evaluating Distributed Coordination in Multi-Agent LLM Systems](https://md.research.elamur.ai/free/en/papers/zhang-2026-silo-bench-scalable-environment-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuzhe Zhang, Feiran Liu, Yi Shan, et al.*2026 · 2 citations* 10. **[ComfyUI-R1: Exploring Reasoning Models for Workflow Generation](https://md.research.elamur.ai/free/en/papers/xu-2026-comfyui-r1-exploring-reasoning-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenran Xu, Yiyu Wang, Xue Yang, et al.*2026 · 1 citation* 11. **[DART: Leveraging Multi-Agent Disagreement for Tool Recruitment in Multimodal Reasoning](https://md.research.elamur.ai/free/en/papers/sivakumaran-2026-dart-leveraging-multi-agent-disagreement/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Nithin Sivakumaran, Justin Chen, David Wan, et al.*2026 · 1 citation* 12. **[InferenceDynamics: Adaptive LLM Routing through Structured Capability and Knowledge Profiling](https://md.research.elamur.ai/free/en/papers/shi-2026-inferencedynamics-adaptive-llm-routing-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haochen Shi, Tianshi Zheng, Weiqi Wang, et al.*2026 · 1 citation* 13. **[A Game-Theoretic Negotiation Framework for Cross-Cultural Consensus](https://md.research.elamur.ai/free/en/papers/zhang-2026-game-theoretic-negotiation-framework-cross/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guoxi Zhang, Jiawei Chen, Tianzhuo Yang, et al.*2026* 14. **[CompTab: A Comprehensive Benchmark for Real-World TableQA with Complex Reasoning and Irregular Tables](https://md.research.elamur.ai/free/en/papers/yang-2026-comptab-comprehensive-benchmark-real-world/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhen Yang, Wei Du, Jie Wang, et al.*2026* 15. **[ConSensus: Multi-Agent Collaboration for Multimodal Sensing](https://md.research.elamur.ai/free/en/papers/yoon-2026-consensus-multi-agent-collaboration-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hyungjun Yoon, Mohammad Malekzadeh, Sung-Ju Lee, et al.*2026* 48 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/wang-2024-rethinking-bounds-llm-reasoning/) — Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?