---
title: "Who cites Large Knowledge Model: Perspectives and Challenges"
description: "42 papers of the Elamur Research library cite «Large Knowledge Model: Perspectives and Challenges», found in their bibliographies; the…"
canonical: "https://research.elamur.ai/free/en/papers/chen-2023-large-knowledge-model-perspectives-challenges/cited-by/"
---
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# Who cites «Large Knowledge Model: Perspectives and Challenges»

42 papers of our library cite it (of the 149,439 whose bibliographies we read) · 9 with a page here, the most cited first · [← back to «Large Knowledge Model: Perspectives and Challenges»](https://md.research.elamur.ai/free/en/papers/chen-2023-large-knowledge-model-perspectives-challenges/)

1. **[Graph Retrieval-Augmented Generation: A Survey](https://md.research.elamur.ai/free/en/papers/peng-2024-graph-retrieval-augmented-generation-survey/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Boci Peng, Yun Zhu, Yongchao Liu, et al.*2024 · 276 citations*
2. **[Mitigating Lost-in-Retrieval Problems in Retrieval Augmented Multi-Hop Question Answering](https://md.research.elamur.ai/free/en/papers/zhu-2025-mitigating-lost-retrieval-problems-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rongzhi Zhu, Xiangyu Liu, Zequn Sun, et al.*2025 · 16 citations*
3. **[RTQA : Recursive Thinking for Complex Temporal Knowledge Graph Question Answering with Large Language Models](https://md.research.elamur.ai/free/en/papers/gong-2025-rtqa-recursive-thinking-complex-temporal/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhaoyan Gong, Juan Li, Zhiqiang Liu, et al.*2025 · 9 citations*
4. **[KnowRL: Exploring Knowledgeable Reinforcement Learning for Factuality](https://md.research.elamur.ai/free/en/papers/ren-2026-knowrl-exploring-knowledgeable-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Baochang Ren, Shuofei Qiao, Ningyu Zhang, et al.*2026 · 5 citations*
5. **[Temp-R1: A Unified Autonomous Agent for Complex Temporal KGQA via Reverse Curriculum Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/gong-2026-temp-r1-unified-autonomous-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaoyan Gong, Zhiqiang Liu, Songze Li, et al.*2026 · 4 citations*
6. **[Enrich-on-Graph: Query-Graph Alignment for Complex Reasoning with LLM Enriching](https://md.research.elamur.ai/free/en/papers/li-2025-enrich-graph-query-graph-alignment/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Songze Li, Zhiqiang Liu, Zhengke Gui, et al.*2025 · 4 citations*
7. **[Why Steering Works: Toward a Unified View of Language Model Parameter Dynamics](https://md.research.elamur.ai/free/en/papers/xu-2026-why-steering-works-unified-view/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziwen Xu, Chenyan WU, Hengyu Sun, et al.*2026 · 1 citation*
8. **[Execution as Verification: Fine-Grained Self-Correcting Reasoning for Complex KBQA](https://md.research.elamur.ai/free/en/papers/zhang-2026-execution-as-verification-fine-grained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minghan Zhang, Zhen Yang, Haodong Zou, et al.*2026*
9. **[How Controllable Are Large Language Models? A Unified Evaluation across Behavioral Granularities](https://md.research.elamur.ai/free/en/papers/xu-2026-how-controllable-are-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziwen Xu, Kewei Xu, Haoming Xu, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/chen-2023-large-knowledge-model-perspectives-challenges/) — Large Knowledge Model: Perspectives and Challenges
