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Hallucinations in large language models (LLMs), plausible but factually inaccurate text, are often viewed as undesirable.
On Faithfulness and Factuality in Abstractive Summarization
Maynez, J.; Narayan, S.; Bohnet, B.; and McDonald, R. 2020 · 1919
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SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules
Weininger, D. 1988 · 1988
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The properties of known drugs. 1. Molecular frameworks
Bemis, G. W.; and Murcko, M. A. 1996 · 1996
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Principles of early drug discovery
Hughes, J. P.; Rees, S.; Kalindjian, S. B.; and Philpott, K. L. 2011 · 2011
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MoleculeNet: a benchmark for molecular machine learning
Wu, Z.; Ramsundar, B.; Feinberg, E. N.; Gomes, J.; Geniesse, C.; Pappu, A. S.; Leswing, K.; and Pande, V. 2018 · 2018
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Counterfactuals in explainable artificial intelligence (XAI): Evidence from human reasoning
Byrne, R. M. 2019 · 2019
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Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models
Wu, T.; Ribeiro, M. T.; Heer, J.; and Weld, D. 2021 · 2021
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CORE: A Retrieve-then-Edit Framework for Counterfactual Data Generation
Dixit, T.; Paranjape, B.; Hajishirzi, H.; and Zettlemoyer, L. 2022 · 2022
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Translation between Molecules and Natural Language
Edwards, C.; Lai, T.; Ros, K.; Honke, G.; Cho, K.; and Ji, H. 2022 · 2022
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Rethinking creativity: creative industries, AI and everyday creativity
Lee, H.-K. 2022 · 2022
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Model agnostic generation of counterfactual explanations for molecules
Wellawatte, G. P.; Seshadri, A.; and White, A. D. 2022 · 2022
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A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity
Bang, Y.; Cahyawijaya, S.; Lee, N.; Dai, W.; Su, D.; Wilie, B.; Lovenia, H.; Ji, Z.; Yu, T.; Chung, W.; Do, Q. V.; Xu, Y.; and Fung, P. 2023 · 2023
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Autonomous chemical research with large language models
Boiko, D. A.; MacKnight, R.; Kline, B.; and Gomes, G. 2023 · 2023
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Artificial intelligence enabled ChatGPT and large language models in drug target discovery, drug discovery, and development
Chakraborty, C.; Bhattacharya, M.; and Lee, S.-S. 2023 · 2023
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Probing the “Creativity” of Large Language Models: Can models produce divergent semantic association?
Chen, H.; and Ding, N. 2023 · 2023
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OpenAGI: When LLM Meets Domain Experts
Ge, Y.; Hua, W.; Mei, K.; ji, j.; Tan, J.; Xu, S.; Li, Z.; and Zhang, Y. 2023 · 2023
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A Confederacy of Models: a Comprehensive Evaluation of LLMs on Creative Writing
Gómez-Rodríguez, C.; and Williams, P. 2023 · 2023
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A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions
Huang, L.; Yu, W.; Ma, W.; Zhong, W.; Feng, Z.; Wang, H.; Chen, Q.; Peng, W.; Feng, X.; Qin, B.; et al. 2023 · 2023
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Towards Mitigating LLM Hallucination via Self Reflection
Ji, Z.; Yu, T.; Xu, Y.; Lee, N.; Ishii, E.; and Fung, P. 2023 · 2023
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A mathematical investigation of hallucination and creativity in GPT models
Lee, M. 2023 · 2023
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Multi-modal molecule structure–text model for text-based retrieval and editing
Liu, S.; Nie, W.; Wang, C.; Lu, J.; Qiao, Z.; Liu, L.; Tang, J.; Xiao, C.; and Anandkumar, A. 2023 · 2023
Cited alongside, same era.
Large language models generate functional protein sequences across diverse families
Madani, A.; Krause, B.; Greene, E. R.; Subramanian, S.; Mohr, B. P.; Holton, J. M.; Olmos, J. L.; Xiong, C.; Sun, Z. Z.; Socher, R.; et al. 2023 · 2023
Cited alongside, same era.
SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models
Manakul, P.; Liusie, A.; and Gales, M. 2023 · 2023
Cited alongside, same era.
LLM Drug Discovery Challenge: A Contest as a Feasibility Study on the Utilization of Large Language Models in Medicinal Chemistry
Murakumo, K.; Yoshikawa, N.; Rikimaru, K.; Nakamura, S.; Furui, K.; Suzuki, T.; Yamasaki, H.; Nishigaya, Y.; Takagi, Y.; and Ohue, M. 2023 · 2023
Cited alongside, same era.
ChatGPT or LLM in next-generation drug discovery and development: pharmaceutical and biotechnology companies can make use of the artificial intelligence-based device for a faster way of drug discovery and development
DrugAgent: Automating AI-aided Drug Discovery Programming through LLM Multi-Agent Collaboration
Liu, S.; Lu, Y.; Chen, S.; Hu, X.; Zhao, J.; Fu, T.; and Zhao, Y. 2024 · 2024
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Is temperature the creativity parameter of large language models?
Peeperkorn, M.; Kouwenhoven, T.; Brown, D.; and Jordanous, A. 2024 · 2024
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A survey on graph counterfactual explanations: definitions, methods, evaluation, and research challenges
Prado-Romero, M. A.; Prenkaj, B.; Stilo, G.; and Giannotti, F. 2024 · 2024
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PairCFR: Enhancing Model Training on Paired Counterfactually Augmented Data through Contrastive Learning
Qiu, X.; Wang, Y.; Guo, X.; Zeng, Z.; Yue, Y.; Feng, Y.; and Miao, C. 2024 · 2024
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The Effect of Sampling Temperature on Problem Solving in Large Language Models
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Pal, S.; Bhattacharya, M.; Islam, M. A.; and Chakraborty, C. 2023 · 2023
Cited alongside, same era.
The Troubling Emergence of Hallucination in Large Language Models - An Extensive Definition, Quantification, and Prescriptive Remediations
Rawte, V.; Chakraborty, S.; Pathak, A.; Sarkar, A.; Tonmoy, S. T. I.; Chadha, A.; Sheth, A.; and Das, A. 2023 · 2023
Cited alongside, same era.
Drug discovery companies are customizing ChatGPT: here’s how
Savage, N. 2023 · 2023
Cited alongside, same era.
Cognitive mirage: A review of hallucinations in large language models
Ye, H.; Liu, T.; Zhang, A.; Hua, W.; and Jia, W. 2023 · 2023
Cited alongside, same era.
Evaluating Generative Models for Graph-to-Text Generation
Yuan, S.; and Faerber, M. 2023 · 2023
Cited alongside, same era.
HHEM-2.1-Open
Bao, F.; Li, M.; Luo, R.; and Mendelevitch, O. 2024 · 2024
Cited alongside, same era.
Counterfactual token generation in large language models
Chatzi, I.; Benz, N. C.; Straitouri, E.; Tsirtsis, S.; and Gomez-Rodriguez, M. 2024 · 2024
Cited alongside, same era.
Chain-of-Verification Reduces Hallucination in Large Language Models
Dhuliawala, S.; Komeili, M.; Xu, J.; Raileanu, R.; Li, X.; Celikyilmaz, A.; and Weston, J. 2024 · 2024
Cited alongside, same era.
Renze, M. 2024 · 2024
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How Random is Random? Evaluating the Randomness and Humaness of LLMs’ Coin Flips
Van Koevering, K.; and Kleinberg, J. 2024 · 2024
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LightHouse: A Survey of AGI Hallucination
Wang, F. 2024 · 2024
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A Survey on Natural Language Counterfactual Generation
Wang, Y.; Qiu, X.; Yue, Y.; Guo, X.; Zeng, Z.; Feng, Y.; and Shen, Z. 2024 · 2024
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A survey on large language model (llm) security and privacy: The good, the bad, and the ugly
Yao, Y.; Duan, J.; Xu, K.; Cai, Y.; Sun, Z.; and Zhang, Y. 2024 · 2024
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HoneyComb: A Flexible LLM-Based Agent System for Materials Science
Zhang, H.; Song, Y.; Hou, Z.; Miret, S.; and Liu, B. 2024b · 2024
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Prompt-based Generation of Natural Language Explanations of Synthetic Lethality for Cancer Drug Discovery
Zhang, K.; Feng, Y.; and Zheng, J. 2024 · 2024
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Assessing and understanding creativity in large language models
Zhao, Y.; Zhang, R.; Li, W.; Huang, D.; Guo, J.; Peng, S.; Hao, Y.; Wen, Y.; Hu, X.; Du, Z.; et al. 2024 · 2024
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Large language models in drug discovery and development: From disease mechanisms to clinical trials
Zheng, Y.; Koh, H. Y.; Yang, M.; Li, L.; May, L. T.; Webb, G. I.; Pan, S.; and Church, G. 2024 · 2024
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Benchmarking large language models for molecule prediction tasks
Zhong, Z.; Zhou, K.; and Mottin, D. 2024 · 2024
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
Guo, D.; Yang, D.; Zhang, H.; Song, J.; Zhang, R.; Xu, R.; Zhu, Q.; Ma, S.; Wang, P.; Bi, X.; et al. 2025 · 2025
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PubChem 2025 update
Kim, S.; Chen, J.; Cheng, T.; and et al. 2025 · 2025
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CoDy: Counterfactual Explainers for Dynamic Graphs
Qu, Z.; Gomm, D.; and Färber, M. 2025 · 2025
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Teufel, J.; Leinweber, A.; and Friederich, P. 2025 · 2025
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MMGCF: generating counterfactual explanations for molecular property prediction via motif rebuild
Zhang, X.; Liu, Q.; and Han, R. 2025 · 2025
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