---
title: "Who cites Prithviraj Sen — 211 papers of our library"
description: "211 papers of the Elamur Research library cite the works of Prithviraj Sen, found in their bibliographies; the most cited first."
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---
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# Who cites Prithviraj Sen

211 citations of their works from 211 papers of our library (of the 149,439 whose bibliographies we read) · 30 with a page here, the most cited first · [← Prithviraj Sen](https://md.research.elamur.ai/free/en/authors/prithviraj-sen/)

1. **[A Comprehensive Survey on Graph Neural Networks](https://md.research.elamur.ai/free/en/papers/wu-2019-comprehensive-survey-graph-neural-networks/) [IEEE Transactions on Neural Networks and Learning Systems](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-neural-networks-and-learning-systems/)**Zonghan Wu, Shirui Pan, Fengwen Chen, et al.*2019 · 10,312 citations*
2. [**Graph Attention Networks arXiv:1710.10903**Petar Veličkovic, Guillem Cucurull, Arantxa Casanova, et al.*2017 · 9,035 citations*](https://md.research.elamur.ai/free/en/papers/veli-vckovic-2017-graph-attention-networks/)
3. [**Semi-Supervised Classification with Graph Convolutional Networks arXiv:1609.02907**Thomas N. Kipf, Max Welling*2016 · 9,023 citations*](https://md.research.elamur.ai/free/en/papers/kipf-2016-semi-supervised-classification-graph-convolutional/)
4. **[Unifying Large Language Models and Knowledge Graphs: A Roadmap](https://md.research.elamur.ai/free/en/papers/pan-2023-unifying-large-language-models-knowledge/) [IEEE Transactions on Knowledge and Data Engineering](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-knowledge-and-data-engineering/)**Shirui Pan, Linhao Luo, Yufei Wang, et al.*2023 · 1,551 citations*
5. [**Fast Graph Representation Learning with PyTorch Geometric arXiv:1903.02428**Matthias Fey, Jan Eric Lenssen*2019 · 1,440 citations*](https://md.research.elamur.ai/free/en/papers/fey-2019-fast-graph-representation-learning-pytorch/)
6. **[Can language models learn from explanations in context?](https://md.research.elamur.ai/free/en/papers/lampinen-2022-can-language-models-learn-explanations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Andrew Lampinen, Ishita Dasgupta, Stephanie Chan, et al.*2022 · 295 citations*
7. [**Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment arXiv:2308.05374**Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li*2023 · 223 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-trustworthy-llms-survey-guideline-evaluating/)
8. **[Towards Faithful Model Explanation in NLP: A Survey](https://md.research.elamur.ai/free/en/papers/lyu-2024-faithful-model-explanation-nlp-survey/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Qing Lyu, Marianna Apidianaki, Chris Callison-Burch*2024 · 197 citations*
9. [**One Embedder, Any Task: Instruction-Finetuned Text Embeddings arXiv:2212.09741**Hongjin Su, Weijia Shi, Jungo Kasai, et al.*2022 · 193 citations*](https://md.research.elamur.ai/free/en/papers/su-2022-one-embedder-any-task-instruction/)
10. [**Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction arXiv:2106.06935**Zhaocheng Zhu, Zuobai Zhang, Louis-Pascal Xhonneux, et al.*2021 · 159 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2021-neural-bellman-ford-networks-general/)
11. **[MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models](https://md.research.elamur.ai/free/en/papers/wen-2024-mindmap-knowledge-graph-prompting-sparks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilin Wen, Zifeng Wang, Jimeng Sun*2024 · 158 citations*
12. [**ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning arXiv:2212.07919**Olga Golovneva, Moya Chen, Spencer Poff, et al.*2022 · 155 citations*](https://md.research.elamur.ai/free/en/papers/golovneva-2022-roscoe-suite-metrics-scoring-step/)
13. [**A Review on Language Models as Knowledge Bases arXiv:2204.06031**Badr AlKhamissi, Millicent Li, Asli Celikyilmaz, et al.*2022 · 150 citations*](https://md.research.elamur.ai/free/en/papers/alkhamissi-2022-review-language-models-knowledge-bases/)
14. [**Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text arXiv:2401.12070**Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, et al.*2024 · 120 citations*](https://md.research.elamur.ai/free/en/papers/hans-2024-spotting-llms-binoculars-zero-shot/)
15. [**Alignment of Language Agents arXiv:2103.14659**Zachary Kenton, Tom Everitt, Laura Weidinger, et al.*2021 · 120 citations*](https://md.research.elamur.ai/free/en/papers/kenton-2021-alignment-language-agents/)
16. [**Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security arXiv:2401.05459**Yuanchun Li, Hao Wen, Weijun Wang, et al.*2024 · 100 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-personal-llm-agents-insights-survey/)
17. **[Explanation-Based Human Debugging of NLP Models: A Survey](https://md.research.elamur.ai/free/en/papers/lertvittayakumjorn-2021-explanation-based-human-debugging-nlp/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Piyawat Lertvittayakumjorn, Francesca Toni*2021 · 77 citations*
18. [**Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning arXiv:2305.19523**Xiaoxin He, Xavier Bresson, Thomas Laurent, et al.*2023 · 75 citations*](https://md.research.elamur.ai/free/en/papers/he-2023-harnessing-explanations-llm-lm-interpreter/)
19. **[DiReCT: Diagnostic Reasoning for Clinical Notes via Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-direct-diagnostic-reasoning-clinical-notes/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Bowen Wang, Jiuyang Chang, Yiming Qian, et al.*2024 · 20 citations*
20. **[Can Graph Descriptive Order Affect Solving Graph Problems with LLMs?](https://md.research.elamur.ai/free/en/papers/ge-2025-can-graph-descriptive-order-affect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuyao Ge, Shenghua Liu, Baolong Bi, et al.*2025 · 10 citations*
21. [**Language Models Fail to Introspect About Their Knowledge of Language arXiv:2503.07513**Siyuan Song, Jennifer Hu, Kyle Mahowald*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/song-2025-language-models-fail-introspect-about/)
22. [**Arabic Sentiment Analysis with Noisy Deep Explainable Model arXiv:2309.13731 · NLPIR 2023: 2023 7th International Conference on Natural Language Processing and Information Retrieval, Seoul, Republic of Korea, December 2023**Md. Atabuzzaman, Md Shajalal, Maksuda Bilkis Baby, et al.*2023 · 5 citations*](https://md.research.elamur.ai/free/en/papers/atabuzzaman-2023-arabic-sentiment-analysis-noisy-deep/)
23. [**From Statistical Relational to Neurosymbolic Artificial Intelligence: a Survey arXiv:2108.11451**Giuseppe Marra, Sebastijan Dumančić, Robin Manhaeve, et al.*2021 · 3 citations*](https://md.research.elamur.ai/free/en/papers/marra-2021-statistical-relational-neurosymbolic-artificial/)
24. **[A Graph Talks, But Who's Listening? Rethinking Evaluations for Graph-Language Models](https://md.research.elamur.ai/free/en/papers/petkar-2026-graph-talks-but-who-s/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Soham Petkar, Hari Aakash K, Anirudh Vempati, et al.*2026 · 1 citation*
25. **[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*
26. **[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*
27. **[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*
28. **[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*
29. **[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*
30. [**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/)

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