{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,2]],"date-time":"2025-10-02T06:04:34Z","timestamp":1759385074800,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":90,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T00:00:00Z","timestamp":1727654400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,9,30]]},"DOI":"10.1145\/3678890.3678906","type":"proceedings-article","created":{"date-parts":[[2024,9,29]],"date-time":"2024-09-29T22:23:36Z","timestamp":1727648616000},"page":"480-495","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["KGDist: A Prompt-Based Distillation Attack against LMs Augmented with Knowledge Graphs"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-5286-1740","authenticated-orcid":false,"given":"Hualong","family":"Ma","sequence":"first","affiliation":[{"name":"SKLOIS, Institute of Information Engineering, Chinese Academy of Sciences, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2671-4314","authenticated-orcid":false,"given":"Peizhuo","family":"Lv","sequence":"additional","affiliation":[{"name":"SKLOIS, Institute of Information Engineering, Chinese Academy of Sciences, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5624-2987","authenticated-orcid":false,"given":"Kai","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute of Information Engineering, Chinese Academy of Sciences, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-1475-8364","authenticated-orcid":false,"given":"Jiachen","family":"Zhou","sequence":"additional","affiliation":[{"name":"SKLOIS, Institute of Information Engineering, Chinese Academy of Sciences, China"}]}],"member":"320","published-online":{"date-parts":[[2024,9,30]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Prompting as Probing: Using Language Models for Knowledge Base Construction. ArXiv abs\/2208.11057","author":"Alivanistos Dimitrios","year":"2022","unstructured":"Dimitrios Alivanistos, Selene\u00a0B\u2019aez Santamar\u2019ia, Michael Cochez, Jan-Christoph Kalo, Emile van Krieken, and Thiviyan Thanapalasingam. 2022. Prompting as Probing: Using Language Models for Knowledge Base Construction. ArXiv abs\/2208.11057 (2022)."},{"key":"e_1_3_2_1_2_1","unstructured":"Michael Atkin. 2023. Knowledge graph implementation: Costs and obstacles to consider. https:\/\/www.ontotext.com\/knowledgehub\/white_paper\/knowledge-graph-implementation-costs-and-obstacles-to-consider\/"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE51399.2021.00202"},{"key":"e_1_3_2_1_4_1","volume-title":"Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods. ArXiv abs\/2111.03120","author":"Bhardwaj Peru","year":"2021","unstructured":"Peru Bhardwaj, John\u00a0D. Kelleher, Luca Costabello, and Declan O\u2019Sullivan. 2021. Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods. ArXiv abs\/2111.03120 (2021)."},{"key":"e_1_3_2_1_5_1","volume-title":"The Unified Medical Language System (UMLS): integrating biomedical terminology. Nucleic acids research 32 Database issue","author":"Bodenreider Olivier","year":"2004","unstructured":"Olivier Bodenreider. 2004. The Unified Medical Language System (UMLS): integrating biomedical terminology. Nucleic acids research 32 Database issue (2004), D267\u201370."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0169-7552(98)00110-X"},{"key":"e_1_3_2_1_7_1","volume-title":"Stealing Part of a Production Language Model. ArXiv abs\/2403.06634","author":"Carlini Nicholas","year":"2024","unstructured":"Nicholas Carlini, Daniel Paleka, Krishnamurthy Dvijotham, Thomas Steinke, Jonathan Hayase, A.\u00a0Feder Cooper, Katherine Lee, Matthew Jagielski, Milad Nasr, Arthur Conmy, Eric Wallace, David Rolnick, and Florian Tram\u00e8r. 2024. Stealing Part of a Production Language Model. ArXiv abs\/2403.06634 (2024). https:\/\/api.semanticscholar.org\/CorpusID:268357903"},{"key":"e_1_3_2_1_8_1","volume-title":"Identifying and Manipulating the Personality Traits of Language Models. ArXiv abs\/2212.10276","author":"Caron Graham","year":"2022","unstructured":"Graham Caron and Shashank Srivastava. 2022. Identifying and Manipulating the Personality Traits of Language Models. ArXiv abs\/2212.10276 (2022). https:\/\/api.semanticscholar.org\/CorpusID:254877016"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Donghyun Choi Myeong\u00a0Cheol Shin EungGyun Kim and Dong\u00a0Ryeol Shin. 2021. OutFlip: Generating Examples for Unknown Intent Detection with Natural Language Attack. In Findings.","DOI":"10.18653\/v1\/2021.findings-acl.45"},{"key":"e_1_3_2_1_10_1","volume-title":"Ultra-Fine Entity Typing. ArXiv abs\/1807.04905","author":"Choi Eunsol","year":"2018","unstructured":"Eunsol Choi, Omer Levy, Yejin Choi, and Luke Zettlemoyer. 2018. Ultra-Fine Entity Typing. ArXiv abs\/1807.04905 (2018)."},{"key":"e_1_3_2_1_11_1","unstructured":"Gautam Chutani. 2024. Unlocking LLM confidence through Logprobs. https:\/\/gautam75.medium.com\/unlocking-llm-confidence-through-logprobs-54b26ed1b48a"},{"key":"e_1_3_2_1_12_1","first-page":"39","article-title":"From \u2019F\u2019 to \u2019A\u2019 on the N.Y. Regents Science Exams: An Overview of the Aristo Project","volume":"41","author":"Clark Peter","year":"2019","unstructured":"Peter Clark, Oren Etzioni, Daniel Khashabi, Tushar Khot, Bhavana Dalvi, Kyle Richardson, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord, Niket Tandon, Sumithra Bhakthavatsalam, Dirk Groeneveld, Michal Guerquin, and Michael Schmitz. 2019. From \u2019F\u2019 to \u2019A\u2019 on the N.Y. Regents Science Exams: An Overview of the Aristo Project. AI Mag. 41 (2019), 39\u201353.","journal-title":"AI Mag."},{"key":"e_1_3_2_1_13_1","volume-title":"Discovering the Hidden Vocabulary of DALLE-2. ArXiv abs\/2206.00169","author":"Daras Giannis","year":"2022","unstructured":"Giannis Daras and Alexandros\u00a0G. Dimakis. 2022. Discovering the Hidden Vocabulary of DALLE-2. ArXiv abs\/2206.00169 (2022)."},{"key":"e_1_3_2_1_14_1","volume-title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. ArXiv abs\/1810.04805","author":"Devlin Jacob","year":"2019","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. ArXiv abs\/1810.04805 (2019)."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20099-1_9"},{"key":"e_1_3_2_1_16_1","volume-title":"From local to global: A graph rag approach to query-focused summarization. arXiv preprint arXiv:2404.16130","author":"Edge Darren","year":"2024","unstructured":"Darren Edge, Ha Trinh, Newman Cheng, Joshua Bradley, Alex Chao, Apurva Mody, Steven Truitt, and Jonathan Larson. 2024. From local to global: A graph rag approach to query-focused summarization. arXiv preprint arXiv:2404.16130 (2024)."},{"key":"e_1_3_2_1_17_1","unstructured":"FactNexus EKG. 2023. Knowledge Graph Enterprise. https:\/\/kgkg.factnexus.com\/@3782\u00a0167.html\/"},{"key":"e_1_3_2_1_18_1","volume-title":"Efficient Pruning of Large Knowledge Graphs. In International Joint Conference on Artificial Intelligence.","author":"Faralli Stefano","year":"2018","unstructured":"Stefano Faralli, Irene Finocchi, Simone\u00a0Paolo Ponzetto, and Paola Velardi. 2018. Efficient Pruning of Large Knowledge Graphs. In International Joint Conference on Artificial Intelligence."},{"key":"e_1_3_2_1_19_1","volume-title":"CodeBERT: A Pre-Trained Model for Programming and Natural Languages. ArXiv abs\/2002.08155","author":"Feng Zhangyin","year":"2020","unstructured":"Zhangyin Feng, Daya Guo, Duyu Tang, Nan Duan, Xiaocheng Feng, Ming Gong, Linjun Shou, Bing Qin, Ting Liu, Daxin Jiang, and Ming Zhou. 2020. CodeBERT: A Pre-Trained Model for Programming and Natural Languages. ArXiv abs\/2002.08155 (2020)."},{"key":"e_1_3_2_1_20_1","volume-title":"PAL: Program-aided Language Models. ArXiv abs\/2211.10435","author":"Gao Luyu","year":"2022","unstructured":"Luyu Gao, Aman Madaan, Shuyan Zhou, Uri Alon, Pengfei Liu, Yiming Yang, Jamie Callan, and Graham Neubig. 2022. PAL: Program-aided Language Models. ArXiv abs\/2211.10435 (2022)."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1649"},{"key":"e_1_3_2_1_22_1","unstructured":"Andrew\u00a0V. Goldberg. 1987. Efficient graph algorithms for sequential and parallel computers. https:\/\/api.semanticscholar.org\/CorpusID:37561100"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.websem.2007.11.011"},{"key":"e_1_3_2_1_24_1","volume-title":"REALM: Retrieval-Augmented Language Model Pre-Training. ArXiv abs\/2002.08909","author":"Guu Kelvin","year":"2020","unstructured":"Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Ming-Wei Chang. 2020. REALM: Retrieval-Augmented Language Model Pre-Training. ArXiv abs\/2002.08909 (2020)."},{"key":"e_1_3_2_1_25_1","volume-title":"Solving Math Word Problems by Combining Language Models With Symbolic Solvers. ArXiv abs\/2304.09102","author":"He-Yueya Joy","year":"2023","unstructured":"Joy He-Yueya, Gabriel Poesia, Rose\u00a0E. Wang, and Noah\u00a0D. Goodman. 2023. Solving Math Word Problems by Combining Language Models With Symbolic Solvers. ArXiv abs\/2304.09102 (2023)."},{"key":"e_1_3_2_1_26_1","volume-title":"Distilling the Knowledge in a Neural Network. ArXiv abs\/1503.02531","author":"Hinton E.","year":"2015","unstructured":"Geoffrey\u00a0E. Hinton, Oriol Vinyals, and Jeffrey Dean. 2015. Distilling the Knowledge in a Neural Network. ArXiv abs\/1503.02531 (2015)."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"crossref","unstructured":"Xiaoqi Jiao Yichun Yin Lifeng Shang Xin Jiang Xiao Chen Linlin Li Fang Wang and Qun Liu. 2019. TinyBERT: Distilling BERT for Natural Language Understanding. In Findings.","DOI":"10.18653\/v1\/2020.findings-emnlp.372"},{"key":"e_1_3_2_1_28_1","unstructured":"Joaogante. 2023. [announcement] generation: Get probabilities for generated output. https:\/\/discuss.huggingface.co\/t\/announcement-generation-get-probabilities-for-generated-output\/30075"},{"key":"e_1_3_2_1_29_1","unstructured":"Darek Kleczek. 2023. A gentle introduction to LLM Apis. https:\/\/wandb.ai\/darek\/llmapps\/reports\/A-Gentle-Introduction-to-LLM-APIs\u2013Vmlldzo0NjM0MTMz"},{"key":"e_1_3_2_1_30_1","volume-title":"International Conference on Semantic Systems.","author":"Knoblach Judith","year":"2022","unstructured":"Judith Knoblach, Nikhil Acharya, Bhavya Koranemkattil, Andreas Both, and Diego Collarana. 2022. Combining Knowledge Graphs and Language Models to Answer Questions over Tables. In International Conference on Semantic Systems."},{"key":"e_1_3_2_1_31_1","volume-title":"Language Models as an Alternative Evaluator of Word Order Hypotheses: A Case Study in Japanese. ArXiv abs\/2005.00842","author":"Kuribayashi Tatsuki","year":"2020","unstructured":"Tatsuki Kuribayashi, Takumi Ito, Jun Suzuki, and Kentaro Inui. 2020. Language Models as an Alternative Evaluator of Word Order Hypotheses: A Case Study in Japanese. ArXiv abs\/2005.00842 (2020). https:\/\/api.semanticscholar.org\/CorpusID:218487721"},{"key":"e_1_3_2_1_32_1","volume-title":"10th USENIX Symposium on Operating Systems Design and Implementation (OSDI 12)","author":"Kyrola Aapo","year":"2012","unstructured":"Aapo Kyrola, Guy Blelloch, and Carlos Guestrin. 2012. GraphChi: Large-Scale Graph Computation on Just a PC. In 10th USENIX Symposium on Operating Systems Design and Implementation (OSDI 12). USENIX Association, Hollywood, CA, 31\u201346. https:\/\/www.usenix.org\/conference\/osdi12\/technical-sessions\/presentation\/kyrola"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3564625.3567969"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.01.139"},{"key":"e_1_3_2_1_35_1","volume-title":"2024 IEEE\/ACM 46th International Conference on Software Engineering (ICSE)","author":"Li Zongjie","year":"2023","unstructured":"Zongjie Li, Chaozheng Wang, Pingchuan Ma, Chaowei Liu, Shuai Wang, Daoyuan Wu, and Cuiyun Gao. 2023. On Extracting Specialized Code Abilities from Large Language Models: A Feasibility Study. 2024 IEEE\/ACM 46th International Conference on Software Engineering (ICSE) (2023), 893\u2013905. https:\/\/api.semanticscholar.org\/CorpusID:257365453"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-021-00911-5"},{"key":"e_1_3_2_1_37_1","volume-title":"Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems","author":"Liu Vivian","year":"2021","unstructured":"Vivian Liu and Lydia\u00a0B. Chilton. 2021. Design Guidelines for Prompt Engineering Text-to-Image Generative Models. Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (2021)."},{"key":"e_1_3_2_1_38_1","volume-title":"RoBERTa: A Robustly Optimized BERT Pretraining Approach. ArXiv abs\/1907.11692","author":"Liu Yinhan","year":"2019","unstructured":"Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019. RoBERTa: A Robustly Optimized BERT Pretraining Approach. ArXiv abs\/1907.11692 (2019)."},{"key":"e_1_3_2_1_39_1","volume-title":"Augmented Language Models: a Survey. ArXiv abs\/2302.07842","author":"Mialon Gr\u00e9goire","year":"2023","unstructured":"Gr\u00e9goire Mialon, Roberto Dess\u00ec, Maria Lomeli, Christoforos Nalmpantis, Ramakanth Pasunuru, Roberta Raileanu, Baptiste Rozi\u00e8re, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, and Thomas Scialom. 2023. Augmented Language Models: a Survey. ArXiv abs\/2302.07842 (2023)."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1260"},{"key":"e_1_3_2_1_41_1","volume-title":"A BFS-Based Pruning Algorithm for Disease-Symptom Knowledge Graph Database. Information and Communication Technology for Intelligent Systems","author":"Mondal Safikureshi","year":"2018","unstructured":"Safikureshi Mondal and Nandini Mukherjee. 2018. A BFS-Based Pruning Algorithm for Disease-Symptom Knowledge Graph Database. Information and Communication Technology for Intelligent Systems (2018). https:\/\/api.semanticscholar.org\/CorpusID:69298160"},{"key":"e_1_3_2_1_42_1","volume-title":"WebGPT: Browser-assisted question-answering with human feedback. ArXiv abs\/2112.09332","author":"Nakano Reiichiro","year":"2021","unstructured":"Reiichiro Nakano, Jacob Hilton, S.\u00a0Arun Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, Xu Jiang, Karl Cobbe, Tyna Eloundou, Gretchen Krueger, Kevin Button, Matthew Knight, Benjamin Chess, and John Schulman. 2021. WebGPT: Browser-assisted question-answering with human feedback. ArXiv abs\/2112.09332 (2021)."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2022.3225217"},{"key":"e_1_3_2_1_44_1","unstructured":"Onotext. 2023. What is a Knowledge Graph?https:\/\/www.ontotext.com\/knowledgehub\/fundamentals\/what-is-a-knowledge-graph\/"},{"key":"e_1_3_2_1_46_1","volume-title":"Knockoff Nets: Stealing Functionality of Black-Box Models. 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Orekondy Tribhuvanesh","year":"2018","unstructured":"Tribhuvanesh Orekondy, Bernt Schiele, and Mario Fritz. 2018. Knockoff Nets: Stealing Functionality of Black-Box Models. 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2018), 4949\u20134958."},{"key":"e_1_3_2_1_47_1","volume-title":"The Web Conference. https:\/\/api.semanticscholar.org\/CorpusID:1508503","author":"Page Lawrence","year":"1999","unstructured":"Lawrence Page, Sergey Brin, Rajeev Motwani, and Terry Winograd. 1999. The PageRank Citation Ranking : Bringing Order to the Web. In The Web Conference. https:\/\/api.semanticscholar.org\/CorpusID:1508503"},{"key":"e_1_3_2_1_48_1","volume-title":"Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security","author":"Papernot Nicolas","year":"2016","unstructured":"Nicolas Papernot, Patrick Mcdaniel, Ian\u00a0J. Goodfellow, Somesh Jha, Z.\u00a0Berkay Celik, and Ananthram Swami. 2016. Practical Black-Box Attacks against Machine Learning. Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security (2016)."},{"key":"e_1_3_2_1_49_1","unstructured":"Sarah Perez. 2012. Wikipedia\u2019s next big thing: Wikidata a machine-readable user-editable database funded by Google Paul Allen and others. https:\/\/techcrunch.com\/2012\/03\/30\/wikipedias-next-big-thing-wikidata-a-machine-readable-user-editable-database-funded-by-google-paul-allen-and-others\/"},{"key":"e_1_3_2_1_50_1","volume-title":"Knowledge Enhanced Contextual Word Representations. In Conference on Empirical Methods in Natural Language Processing.","author":"Peters E.","year":"2019","unstructured":"Matthew\u00a0E. Peters, Mark Neumann, IV RobertL.Logan, Roy Schwartz, Vidur Joshi, Sameer Singh, and Noah\u00a0A. Smith. 2019. Knowledge Enhanced Contextual Word Representations. In Conference on Empirical Methods in Natural Language Processing."},{"key":"e_1_3_2_1_51_1","volume-title":"Language Models as Knowledge Bases?ArXiv abs\/1909.01066","author":"Petroni Fabio","year":"2019","unstructured":"Fabio Petroni, Tim Rockt\u00e4schel, Patrick Lewis, Anton Bakhtin, Yuxiang Wu, Alexander\u00a0H. Miller, and Sebastian Riedel. 2019. Language Models as Knowledge Bases?ArXiv abs\/1909.01066 (2019)."},{"key":"e_1_3_2_1_52_1","unstructured":"Mohammad\u00a0Taher Pilehvar and Jos\u00e9 Camacho-Collados. 2018. WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representations. In North American Chapter of the Association for Computational Linguistics."},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"crossref","unstructured":"Nina Poerner Ulli Waltinger and Hinrich Sch\u00fctze. 2019. E-BERT: Efficient-Yet-Effective Entity Embeddings for BERT. In Findings.","DOI":"10.18653\/v1\/2020.findings-emnlp.71"},{"key":"e_1_3_2_1_54_1","volume-title":"Word Order Does Matter and Shuffled Language Models Know It. In Annual Meeting of the Association for Computational Linguistics. https:\/\/api.semanticscholar.org\/CorpusID:247594659","author":"Ravishankar Vinit","year":"2022","unstructured":"Vinit Ravishankar, Mostafa Abdou, Artur Kulmizev, and Anders S\u00f8gaard. 2022. Word Order Does Matter and Shuffled Language Models Know It. In Annual Meeting of the Association for Computational Linguistics. https:\/\/api.semanticscholar.org\/CorpusID:247594659"},{"key":"e_1_3_2_1_55_1","unstructured":"[55] Randy Rockinson. 2023. https:\/\/blog.google\/products\/shopping\/shopping-graph-explained\/"},{"key":"e_1_3_2_1_56_1","volume-title":"Learning a Health Knowledge Graph from Electronic Medical Records. Scientific Reports 7","author":"Rotmensch Maya","year":"2017","unstructured":"Maya Rotmensch, Yoni Halpern, Abdulhakim Tlimat, Steven Horng, and David\u00a0A. Sontag. 2017. Learning a Health Knowledge Graph from Electronic Medical Records. Scientific Reports 7 (2017)."},{"key":"e_1_3_2_1_57_1","volume-title":"a distilled version of BERT: smaller, faster, cheaper and lighter. ArXiv abs\/1910.01108","author":"Sanh Victor","year":"2019","unstructured":"Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019. DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter. ArXiv abs\/1910.01108 (2019)."},{"key":"e_1_3_2_1_58_1","volume-title":"Sponge Examples: Energy-Latency Attacks on Neural Networks. 2021 IEEE European Symposium on Security and Privacy (EuroS&P)","author":"Shumailov Ilia","year":"2020","unstructured":"Ilia Shumailov, Yiren Zhao, Daniel Bates, Nicolas Papernot, Robert\u00a0D. Mullins, and Ross Anderson. 2020. Sponge Examples: Energy-Latency Attacks on Neural Networks. 2021 IEEE European Symposium on Security and Privacy (EuroS&P) (2020), 212\u2013231."},{"key":"e_1_3_2_1_59_1","volume-title":"An Open Multilingual Graph of General Knowledge. ArXiv abs\/1612.03975","author":"Speer Robyn","year":"2016","unstructured":"Robyn Speer, Joshua Chin, and Catherine Havasi. 2016. ConceptNet 5.5: An Open Multilingual Graph of General Knowledge. ArXiv abs\/1612.03975 (2016)."},{"key":"e_1_3_2_1_60_1","first-page":"1146","article-title":"Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation with Large Language Models","volume":"29","author":"Strobelt Hendrik","year":"2022","unstructured":"Hendrik Strobelt, Albert Webson, Victor Sanh, Benjamin Hoover, Johanna Beyer, Hanspeter Pfister, and Alexander\u00a0M. Rush. 2022. Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation with Large Language Models. IEEE Transactions on Visualization and Computer Graphics 29 (2022), 1146\u20131156.","journal-title":"IEEE Transactions on Visualization and Computer Graphics"},{"key":"e_1_3_2_1_61_1","volume-title":"Interpreting Language Models Through Knowledge Graph Extraction. ArXiv abs\/2111.08546","author":"Swamy Vinitra","year":"2021","unstructured":"Vinitra Swamy, Angelika Romanou, and Martin Jaggi. 2021. Interpreting Language Models Through Knowledge Graph Extraction. ArXiv abs\/2111.08546 (2021)."},{"key":"e_1_3_2_1_62_1","volume-title":"Distilling Task-Specific Knowledge from BERT into Simple Neural Networks. ArXiv abs\/1903.12136","author":"Tang Raphael","year":"2019","unstructured":"Raphael Tang, Yao Lu, Linqing Liu, Lili Mou, Olga Vechtomova, and Jimmy\u00a0J. Lin. 2019. Distilling Task-Specific Knowledge from BERT into Simple Neural Networks. ArXiv abs\/1903.12136 (2019). https:\/\/api.semanticscholar.org\/CorpusID:85543565"},{"key":"e_1_3_2_1_63_1","volume-title":"Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs. In International Conference on Machine Learning.","author":"Trivedi S.","year":"2017","unstructured":"Rakshit\u00a0S. Trivedi, Hanjun Dai, Yichen Wang, and Le Song. 2017. Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs. In International Conference on Machine Learning."},{"key":"e_1_3_2_1_64_1","unstructured":"Mike Tung. 2023. Grounded natural language generation with knowledge graphs. https:\/\/blog.diffbot.com\/grounded-natural-language-generation-with-knowledge-graphs\/"},{"key":"e_1_3_2_1_65_1","volume-title":"KOGNAC: Efficient Encoding of Large Knowledge Graphs. ArXiv abs\/1604.04795","author":"Urbani Jacopo","year":"2016","unstructured":"Jacopo Urbani, Sourav Dutta, Sairam Gurajada, and Gerhard Weikum. 2016. KOGNAC: Efficient Encoding of Large Knowledge Graphs. ArXiv abs\/1604.04795 (2016)."},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1145\/2629489"},{"key":"e_1_3_2_1_67_1","doi-asserted-by":"crossref","unstructured":"Qingyun Wang Manling Li Xuan Wang Nikolaus\u00a0Nova Parulian Guangxing Han Jiawei Ma Jingxuan Tu Ying Lin H. Zhang Weili Liu Aabhas Chauhan Yingjun Guan Bangzheng Li Ruisong Li Xiangchen Song Heng Ji Jiawei Han Shih-Fu Chang James Pustejovsky David Liem Ahmed Elsayed Martha Palmer Jasmine Rah Cynthia Schneider and Boyan\u00a0A. Onyshkevych. 2020. COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation. In North American Chapter of the Association for Computational Linguistics.","DOI":"10.18653\/v1\/2021.naacl-demos.8"},{"key":"e_1_3_2_1_68_1","volume-title":"GraphWalker: An I\/O-Efficient and Resource-Friendly Graph Analytic System for Fast and Scalable Random Walks. In USENIX Annual Technical Conference. https:\/\/api.semanticscholar.org\/CorpusID:220657879","author":"Wang Rui","year":"2020","unstructured":"Rui Wang, Yongkun Li, Hong Xie, Yinlong Xu, and John\u00a0C.S. Lui. 2020. GraphWalker: An I\/O-Efficient and Resource-Friendly Graph Analytic System for Fast and Scalable Random Walks. In USENIX Annual Technical Conference. https:\/\/api.semanticscholar.org\/CorpusID:220657879"},{"key":"e_1_3_2_1_69_1","doi-asserted-by":"crossref","unstructured":"Ruize Wang Duyu Tang Nan Duan Zhongyu Wei Xuanjing Huang Jianshu Ji Guihong Cao Daxin Jiang and Ming Zhou. 2020. K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters. In Findings.","DOI":"10.18653\/v1\/2021.findings-acl.121"},{"key":"e_1_3_2_1_70_1","volume-title":"MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers. ArXiv abs\/2002.10957","author":"Wang Wenhui","year":"2020","unstructured":"Wenhui Wang, Furu Wei, Li Dong, Hangbo Bao, Nan Yang, and Ming Zhou. 2020. MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers. ArXiv abs\/2002.10957 (2020). https:\/\/api.semanticscholar.org\/CorpusID:211296536"},{"key":"e_1_3_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00360"},{"key":"e_1_3_2_1_72_1","volume-title":"Mindmap: Knowledge graph prompting sparks graph of thoughts in large language models. arXiv preprint arXiv:2308.09729","author":"Wen Yilin","year":"2023","unstructured":"Yilin Wen, Zifeng Wang, and Jimeng Sun. 2023. Mindmap: Knowledge graph prompting sparks graph of thoughts in large language models. arXiv preprint arXiv:2308.09729 (2023)."},{"key":"e_1_3_2_1_73_1","unstructured":"Wikidata. 2023. Wikidata:statistics - wikidata. https:\/\/www.wikidata.org\/wiki\/Wikidata:Statistics"},{"key":"e_1_3_2_1_74_1","volume-title":"The Free Encyclopedia. https:\/\/en.wikipedia.org\/w\/index.php?title=Open_Mind_Common_Sense&oldid=1124381133 [Online","author":"Wikipedia","year":"2023","unstructured":"Wikipedia contributors. 2022. Open Mind Common Sense \u2014 Wikipedia, The Free Encyclopedia. https:\/\/en.wikipedia.org\/w\/index.php?title=Open_Mind_Common_Sense&oldid=1124381133 [Online; accessed 13-May-2023]."},{"key":"e_1_3_2_1_75_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2023.119406"},{"key":"e_1_3_2_1_76_1","doi-asserted-by":"publisher","DOI":"10.1162\/dint_a_00017"},{"key":"e_1_3_2_1_77_1","unstructured":"Zhilin Yang Zihang Dai Yiming Yang Jaime\u00a0G. Carbonell Ruslan Salakhutdinov and Quoc\u00a0V. Le. 2019. XLNet: Generalized Autoregressive Pretraining for Language Understanding. In Neural Information Processing Systems."},{"key":"e_1_3_2_1_78_1","volume-title":"Advances in Neural Information Processing Systems, S.\u00a0Koyejo, S.\u00a0Mohamed, A.\u00a0Agarwal, D.\u00a0Belgrave, K.\u00a0Cho, and A.\u00a0Oh (Eds.). Vol.\u00a035. Curran Associates","author":"Yao Shunyu","year":"2074","unstructured":"Shunyu Yao, Howard Chen, John Yang, and Karthik Narasimhan. 2022. WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents. In Advances in Neural Information Processing Systems, S.\u00a0Koyejo, S.\u00a0Mohamed, A.\u00a0Agarwal, D.\u00a0Belgrave, K.\u00a0Cho, and A.\u00a0Oh (Eds.). Vol.\u00a035. Curran Associates, Inc., 20744\u201320757. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2022\/file\/82ad13ec01f9fe44c01cb91814fd7b8c-Paper-Conference.pdf"},{"key":"e_1_3_2_1_79_1","volume-title":"ReAct: Synergizing Reasoning and Acting in Language Models. ArXiv abs\/2210.03629","author":"Yao Shunyu","year":"2022","unstructured":"Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2022. ReAct: Synergizing Reasoning and Acting in Language Models. ArXiv abs\/2210.03629 (2022)."},{"key":"e_1_3_2_1_80_1","volume-title":"Deep Bidirectional Language-Knowledge Graph Pretraining. ArXiv abs\/2210.09338","author":"Yasunaga Michihiro","year":"2022","unstructured":"Michihiro Yasunaga, Antoine Bosselut, Hongyu Ren, Xikun Zhang, Christopher\u00a0D. Manning, Percy Liang, and Jure Leskovec. 2022. Deep Bidirectional Language-Knowledge Graph Pretraining. ArXiv abs\/2210.09338 (2022). https:\/\/api.semanticscholar.org\/CorpusID:252968266"},{"key":"e_1_3_2_1_81_1","volume-title":"QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering. ArXiv abs\/2104.06378","author":"Yasunaga Michihiro","year":"2021","unstructured":"Michihiro Yasunaga, Hongyu Ren, Antoine Bosselut, Percy Liang, and Jure Leskovec. 2021. QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering. ArXiv abs\/2104.06378 (2021)."},{"key":"e_1_3_2_1_82_1","volume-title":"Learning With Single-Teacher Multi-Student. In AAAI Conference on Artificial Intelligence.","author":"You Shan","year":"2018","unstructured":"Shan You, Chang Xu, Chao Xu, and Dacheng Tao. 2018. Learning With Single-Teacher Multi-Student. In AAAI Conference on Artificial Intelligence."},{"key":"e_1_3_2_1_83_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583203"},{"key":"e_1_3_2_1_84_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/674"},{"key":"e_1_3_2_1_85_1","volume-title":"Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners. ArXiv abs\/2108.13161","author":"Zhang Ningyu","year":"2021","unstructured":"Ningyu Zhang, Luoqiu Li, Xiang Chen, Shumin Deng, Zhen Bi, Chuanqi Tan, Fei Huang, and Huajun Chen. 2021. Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners. ArXiv abs\/2108.13161 (2021)."},{"key":"e_1_3_2_1_86_1","volume-title":"OPT: Open Pre-trained Transformer Language Models. ArXiv abs\/2205.01068","author":"Zhang Susan","year":"2022","unstructured":"Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi\u00a0Victoria Lin, Todor Mihaylov, Myle Ott, Sam Shleifer, Kurt Shuster, Daniel Simig, Punit\u00a0Singh Koura, Anjali Sridhar, Tianlu Wang, and Luke Zettlemoyer. 2022. OPT: Open Pre-trained Transformer Language Models. ArXiv abs\/2205.01068 (2022)."},{"key":"e_1_3_2_1_87_1","volume-title":"GreaseLM: Graph REASoning Enhanced Language Models. In International Conference on Learning Representations.","author":"Zhang Xikun","year":"2022","unstructured":"Xikun Zhang, Antoine Bosselut, Michihiro Yasunaga, Hongyu Ren, Percy Liang, Christopher\u00a0D. Manning, and Jure Leskovec. 2022. GreaseLM: Graph REASoning Enhanced Language Models. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_88_1","volume-title":"ERNIE: Enhanced Language Representation with Informative Entities. In Annual Meeting of the Association for Computational Linguistics.","author":"Zhang Zhengyan","year":"2019","unstructured":"Zhengyan Zhang, Xu Han, Zhiyuan Liu, Xin Jiang, Maosong Sun, and Qun Liu. 2019. ERNIE: Enhanced Language Representation with Informative Entities. In Annual Meeting of the Association for Computational Linguistics."},{"key":"e_1_3_2_1_89_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.432"},{"key":"e_1_3_2_1_90_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482402"},{"key":"e_1_3_2_1_91_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-022-01653-1"}],"event":{"name":"RAID '24: The 27th International Symposium on Research in Attacks, Intrusions and Defenses","acronym":"RAID '24","location":"Padua Italy"},"container-title":["The 27th International Symposium on Research in Attacks, Intrusions and Defenses"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3678890.3678906","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3678890.3678906","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:18:00Z","timestamp":1750295880000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3678890.3678906"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,30]]},"references-count":90,"alternative-id":["10.1145\/3678890.3678906","10.1145\/3678890"],"URL":"https:\/\/doi.org\/10.1145\/3678890.3678906","relation":{},"subject":[],"published":{"date-parts":[[2024,9,30]]},"assertion":[{"value":"2024-09-30","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}