--- title: "Who cites Harnessing Explanations: — 59 citing papers" description: "59 papers of the Elamur Research library cite «Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph…" canonical: "https://research.elamur.ai/free/en/papers/he-2023-harnessing-explanations-llm-lm-interpreter/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/he-2023-harnessing-explanations-llm-lm-interpreter/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Harnessing Explanations: LLM-to-LM Interpreter…](https://md.research.elamur.ai/free/en/papers/he-2023-harnessing-explanations-llm-lm-interpreter/) / cited by # Who cites «Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning» 59 papers of our library cite it (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · [← back to «Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning»](https://md.research.elamur.ai/free/en/papers/he-2023-harnessing-explanations-llm-lm-interpreter/) 1. **[GraphGPT: Graph Instruction Tuning for Large Language Models](https://md.research.elamur.ai/free/en/papers/tang-2023-graphgpt-graph-instruction-tuning-large/) [International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)](https://md.research.elamur.ai/free/en/venues/international-acm-sigir-conference-on-research-and-development-in-information/)**Jiabin Tang, Yuhao Yang, Wei Wei, et al.*2023 · 268 citations* 2. **[G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering](https://md.research.elamur.ai/free/en/papers/he-2024-g-retriever-retrieval-augmented-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoxin He, Yijun Tian, Yifei Sun, et al.*2024 · 236 citations* 3. **[Taming Language Models for Text-attributed Graph Learning with Decoupled Aggregation](https://md.research.elamur.ai/free/en/papers/zhou-2025-taming-language-models-text-attributed/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chuang Zhou, Zhu Wang, Shengyuan Chen, et al.*2025 · 9 citations* 4. **[Exploring Graph Learning Tasks with Pure LLMs: A Comprehensive Benchmark and Investigation](https://md.research.elamur.ai/free/en/papers/wang-2026-exploring-graph-learning-tasks-pure/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxiang Wang, Xinnan Dai, Wenqi Fan, et al.*2026 · 1 citation* 5. **[AgentGL: Towards Agentic Graph Learning with LLMs via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/sun-2026-agentgl-agentic-graph-learning-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanfu Sun, Kang Li, Dongzhe Fan, et al.*2026* 6. **[CITE: Benchmarking Heterogeneous Text-Attributed Graph Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-cite-benchmarking-heterogeneous-text-attributed/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenghao Zhang, Qingqing Long, Ludi Wang, et al.*2026* 7. **[Generalizable LLM Learning of Graph Synthetic Data with Post-training Alignment](https://md.research.elamur.ai/free/en/papers/zhang-2026-generalizable-llm-learning-graph-synthetic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yizhuo Zhang, Heng Wang, Shangbin Feng, et al.*2026* 8. **[Graph-Based Alternatives to LLMs for Human Simulation](https://md.research.elamur.ai/free/en/papers/suh-2026-graph-based-alternatives-llms-human/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joseph Suh, Suhong Moon, Serina Chang*2026* 9. **[How to Make LMs Strong Node Classifiers?](https://md.research.elamur.ai/free/en/papers/xu-2026-how-make-lms-strong-node/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhe Xu, Kaveh Hassani, Si Zhang, et al.*2026* 10. **[Mitigating Degree Bias in Hypergraphs via Attribute-as-Structure Approach](https://md.research.elamur.ai/free/en/papers/nishide-2026-mitigating-degree-bias-hypergraphs-attribute/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Ryusei Nishide, Makoto Miwa*2026* 11. **[MuSe: Multi-Stage Graph Reasoning via Vision-Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-muse-multi-stage-graph-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanyu Wang, Xu Chu, Zhijie Tan, et al.*2026* 12. [**Recent Advances in Text-attributed Graph Learning via Large Models (大模型驱动的文本属性图学习研究进展) Acta Automatica Sinica (自动化学报)**Yanping Zheng (郑艳萍), Jiarui Ji (季嘉蕊), Yuwei Hu (胡雨韦), et al.*2026*](https://md.research.elamur.ai/free/en/papers/zheng-2026-recent-advances-text/) 13. **[TRN-R1-Zero: Text-rich Network Reasoning via LLMs with Reinforcement Learning Only](https://md.research.elamur.ai/free/en/papers/liu-2026-trn-r1-zero-text-rich/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilun Liu, Ruihong Qiu, Zi Huang*2026* 46 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/he-2023-harnessing-explanations-llm-lm-interpreter/) — Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning