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Misinformation such as fake news and rumors is a serious threat on information ecosystems and public trust.
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AI model GPT-3 (dis)informs us better than humans
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Ghostbuster: Detecting Text Ghostwritten by Large Language Models
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Scientific Fact-Checking: A Survey of Resources and Approaches
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Attacking Fake News Detectors via Manipulating News Social Engagement
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Explainable Claim Verification via Knowledge-Grounded Reasoning with Large Language Models
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FinD: Fine-grained discrepancy-based fake news detection enhanced by event abstract generation
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A Survey on Large Language Model based Autonomous Agents
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Towards Codable Text Watermarking for Large Language Models
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Security and Privacy on Generative Data in AIGC: A Survey
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All Languages Matter: On the Multilingual Safety of Large Language Models
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Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMs
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Self-Knowledge Guided Retrieval Augmentation for Large Language Models
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Aligning Large Language Models with Human: A Survey
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Implementing BERT and fine-tuned RobertA to detect AI generated news by ChatGPT
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Artifcial intelligence-friend or foe in fake news campaigns
Krzysztof Węcel, Marcin Sawiński, Milena Stróżyna, Włodzimierz Lewoniewski, Piotr Stolarski, Ewelina Księżniak, and Witold Abramowicz. 2023 · 2023
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Skywork: A More Open Bilingual Foundation Model
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PolyLM: An Open Source Polyglot Large Language Model
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Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations
Zeming Wei, Yifei Wang, and Yisen Wang. 2023a · 2023
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Sociotechnical Safety Evaluation of Generative AI Systems
Laura Weidinger, Maribeth Rauh, Nahema Marchal, Arianna Manzini, Lisa Anne Hendricks, Juan Mateos-Garcia, Stevie Bergman, Jackie Kay, Conor Griffin, Ben Bariach, Iason Gabriel, Verena Rieser, and William Isaac. 2023 · 2023
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"According to …" Prompting Language Models Improves Quoting from Pre-Training Data
Orion Weller, Marc Marone, Nathaniel Weir, Dawn Lawrie, Daniel Khashabi, and Benjamin Van Durme. 2023 · 2023
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Cheap-fake Detection with LLM using Prompt Engineering
Guangyang Wu, Weijie Wu, Xiaohong Liu, Kele Xu, Tianjiao Wan, and Wenyi Wang. 2023e · 2023
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AI-Generated Content (AIGC): A Survey
Jiayang Wu, Wensheng Gan, Zefeng Chen, Shicheng Wan, and Hong Lin. 2023b · 2023
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Fake News in Sheep’s Clothing: Robust Fake News Detection Against LLM-Empowered Style Attacks
Jiaying Wu and Bryan Hooi. 2023b · 2023
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Prompt-and-Align: Prompt-Based Social Alignment for Few-Shot Fake News Detection
Jiaying Wu, Shen Li, Ailin Deng, Miao Xiong, and Bryan Hooi. 2023c · 2023
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A Survey on LLM-generated Text Detection: Necessity, Methods, and Future Directions
Junchao Wu, Shu Yang, Runzhe Zhan, Yulin Yuan, Derek F. Wong, and Lidia S. Chao. 2023f · 2023
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LLMDet: A Large Language Models Detection Tool
Kangxi Wu, Liang Pang, Huawei Shen, Xueqi Cheng, and Tat-Seng Chua. 2023d · 2023
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AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework
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A Comprehensive Review and Systematic Analysis of Artificial Intelligence Regulation Policies
Weiyue Wu and Shaoshan Liu. 2023 · 2023
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The Rise and Potential of Large Language Model Based Agents: A Survey
Zhiheng Xi, Wenxiang Chen, Xin Guo, Wei He, Yiwen Ding, Boyang Hong, Ming Zhang, Junzhe Wang, Senjie Jin, Enyu Zhou, Rui Zheng, Xiaoran Fan, Xiao Wang, Limao Xiong, Qin Liu, Yuhao Zhou, Weiran Wang, Changhao Jiang, Yicheng Zou, Xiangyang Liu, Zhangyue Yin, Shihan Dou, Rongxiang Weng, Wensen Cheng, Qi Zhang, Wenjuan Qin, Yongyan Zheng, Xipeng Qiu, Xuanjing Huan, and Tao Gui. 2023 · 2023
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The Challenges of Machine Learning for Trust and Safety: A Case Study on Misinformation Detection
Madelyne Xiao and Jonathan Mayer. 2023 · 2023
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Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs
Miao Xiong, Zhiyuan Hu, Xinyang Lu, Yifei Li, Jie Fu, Junxian He, and Bryan Hooi. 2023 · 2023
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Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and Beyond
Fangzhi Xu, Qika Lin, Jiawei Han, Tianzhe Zhao, Jun Liu, and Erik Cambria. 2023a · 2023
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CValues: Measuring the Values of Chinese Large Language Models from Safety to Responsibility
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On the Generalization of Training-based ChatGPT Detection Methods
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Counterfactual Debiasing for Fact Verification. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . Association for Computational Linguistics, Toronto, Canada, 6777–6789
Weizhi Xu, Qiang Liu, Shu Wu, and Liang Wang. 2023b · 2023
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Lemur: Harmonizing Natural Language and Code for Language Agents
Yiheng Xu, Hongjin Su, Chen Xing, Boyu Mi, Qian Liu, Weijia Shi, Binyuan Hui, Fan Zhou, Yitao Liu, Tianbao Xie, Zhoujun Cheng, Siheng Zhao, Lingpeng Kong, Bailin Wang, Caiming Xiong, and Tao Yu. 2023e · 2023
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Virtual Prompt Injection for Instruction-Tuned Large Language Models
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Towards Code Watermarking with Dual-Channel Transformations
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Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond
Jingfeng Yang, Hongye Jin, Ruixiang Tang, Xiaotian Han, Qizhang Feng, Haoming Jiang, Bing Yin, and Xia Hu. 2023d · 2023
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Anatomy of an AI-powered malicious social botnet
Kai-Cheng Yang and Filippo Menczer. 2023 · 2023
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Entity-Aware Dual Co-Attention Network for Fake News Detection. In Findings of the Association for Computational Linguistics: EACL 2023 . Association for Computational Linguistics, Dubrovnik, Croatia, 106–113
Sin-han Yang, Chung-chi Chen, Hen-Hsen Huang, and Hsin-Hsi Chen. 2023a · 2023
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Watermarking Text Generated by Black-Box Language Models
Xi Yang, Kejiang Chen, Weiming Zhang, Chang Liu, Yuang Qi, Jie Zhang, Han Fang, and Nenghai Yu. 2023b · 2023
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DNA-GPT: Divergent N-Gram Analysis for Training-Free Detection of GPT-Generated Text
Xianjun Yang, Wei Cheng, Linda Petzold, William Yang Wang, and Haifeng Chen. 2023c · 2023
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A Survey on Detection of LLMs-Generated Content
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Shadow Alignment: The Ease of Subverting Safely-Aligned Language Models
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The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)
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FuzzLLM: A Novel and Universal Fuzzing Framework for Proactively Discovering Jailbreak Vulnerabilities in Large Language Models
Dongyu Yao, Jianshu Zhang, Ian G. Harris, and Marcel Carlsson. 2023d · 2023
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From Instructions to Intrinsic Human Values - A Survey of Alignment Goals for Big Models
Jing Yao, Xiaoyuan Yi, Xiting Wang, Jindong Wang, and Xing Xie. 2023c · 2023
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LLM Lies: Hallucinations are not Bugs, but Features as Adversarial Examples
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Editing Large Language Models: Problems, Methods, and Opportunities
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Cognitive Mirage: A Review of Hallucinations in Large Language Models
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Do Large Language Models Know What They Don’t Know?. In Findings of the Association for Computational Linguistics: ACL 2023 . Association for Computational Linguistics, Toronto, Canada, 8653–8665
Zhangyue Yin, Qiushi Sun, Qipeng Guo, Jiawen Wu, Xipeng Qiu, and Xuanjing Huang. 2023b · 2023
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Low-Resource Languages Jailbreak GPT-4
Zheng-Xin Yong, Cristina Menghini, and Stephen H. Bach. 2023 · 2023
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Robust Multi-bit Natural Language Watermarking through Invariant Features
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Making Retrieval-Augmented Language Models Robust to Irrelevant Context
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Ferret: Refer and Ground Anything Anywhere at Any Granularity
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GPTFUZZER : Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts
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KoLA: Carefully Benchmarking World Knowledge of Large Language Models
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CHEAT: A Large-scale Dataset for Detecting ChatGPT-writtEn AbsTracts
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Towards Better Chain-of-Thought Prompting Strategies: A Survey
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CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets
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GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher
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MetaAdapt: Domain Adaptive Few-Shot Misinformation Detection via Meta Learning. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . Association for Computational Linguistics, Toronto, Canada, 5223–5239
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Prompt to be Consistent is Better than Self-Consistent? Few-Shot and Zero-Shot Fact Verification with Pre-trained Language Models
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Using Large Language Models for Knowledge Engineering (LLMKE): A Case Study on Wikidata
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One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era
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Extractive Summarization via ChatGPT for Faithful Summary Generation
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How Language Model Hallucinations Can Snowball
Muru Zhang, Ofir Press, William Merrill, Alisa Liu, and Noah A. Smith. 2023i · 2023
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Pan Zhang, Xiaoyi Dong Bin Wang, Yuhang Cao, Chao Xu, Linke Ouyang, Zhiyuan Zhao, Shuangrui Ding, Songyang Zhang, Haodong Duan, Hang Yan, et al · 2023
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Retrieve Anything To Augment Large Language Models
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Mitigating Language Model Hallucination with Interactive Question-Knowledge Alignment
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Interpretable Unified Language Checking
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M3Exam: A Multilingual, Multimodal, Multilevel Benchmark for Examining Large Language Models
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Towards LLM-based Fact Verification on News Claims with a Hierarchical Step-by-Step Prompting Method
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Siren’s Song in the AI Ocean: A Survey on Hallucination in Large Language Models
Yue Zhang, Yafu Li, Leyang Cui, Deng Cai, Lemao Liu, Tingchen Fu, Xinting Huang, Enbo Zhao, Yu Zhang, Yulong Chen, Longyue Wang, Anh Tuan Luu, Wei Bi, Freda Shi, and Shuming Shi. 2023e · 2023
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INO at Factify 2: Structure Coherence based Multi-Modal Fact Verification
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Detecting Out-of-Context Multimodal Misinformation with interpretable neural-symbolic model
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How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances
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SafetyBench: Evaluating the Safety of Large Language Models with Multiple Choice Questions
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Retrieving Multimodal Information for Augmented Generation: A Survey
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A Survey of Large Language Models
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Provable Robust Watermarking for AI-Generated Text
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MiniGPT-5: Interleaved Vision-and-Language Generation via Generative Vokens
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Secrets of RLHF in Large Language Models Part I: PPO
Rui Zheng, Shihan Dou, Songyang Gao, Yuan Hua, Wei Shen, Binghai Wang, Yan Liu, Senjie Jin, Qin Liu, Yuhao Zhou, Limao Xiong, Lu Chen, Zhiheng Xi, Nuo Xu, Wenbin Lai, Minghao Zhu, Cheng Chang, Zhangyue Yin, Rongxiang Weng, Wensen Cheng, Haoran Huang, Tianxiang Sun, Hang Yan, Tao Gui, Qi Zhang, Xipeng Qiu, and Xuanjing Huang. 2023a · 2023
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LIMA: Less Is More for Alignment
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Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems . 1–20
Jiawei Zhou, Yixuan Zhang, Qianni Luo, Andrea G Parker, and Munmun De Choudhury. 2023c · 2023
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Agents: An Open-source Framework for Autonomous Language Agents
Wangchunshu Zhou, Yuchen Eleanor Jiang, Long Li, Jialong Wu, Tiannan Wang, Shi Qiu, Jintian Zhang, Jing Chen, Ruipu Wu, Shuai Wang, Shiding Zhu, Jiyu Chen, Wentao Zhang, Ningyu Zhang, Huajun Chen, Peng Cui, and Mrinmaya Sachan. 2023a · 2023
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MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models
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PromptBench: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts
Kaijie Zhu, Jindong Wang, Jiaheng Zhou, Zichen Wang, Hao Chen, Yidong Wang, Linyi Yang, Wei Ye, Neil Zhenqiang Gong, Yue Zhang, and Xing Xie. 2023b · 2023
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Exploring AI Ethics of ChatGPT: A Diagnostic Analysis
Terry Yue Zhuo, Yujin Huang, Chunyang Chen, and Zhenchang Xing. 2023 · 2023
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Representation Engineering: A Top-Down Approach to AI Transparency
Andy Zou, Long Phan, Sarah Chen, James Campbell, Phillip Guo, Richard Ren, Alexander Pan, Xuwang Yin, Mantas Mazeika, Ann-Kathrin Dombrowski, Shashwat Goel, Nathaniel Li, Michael J. Byun, Zifan Wang, Alex Mallen, Steven Basart, Sanmi Koyejo, Dawn Song, Matt Fredrikson, J. Zico Kolter, and Dan Hendrycks. 2023a · 2023
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Decker: Double Check with Heterogeneous Knowledge for Commonsense Fact Verification
Anni Zou, Zhuosheng Zhang, and Hai Zhao. 2023b · 2023
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Rumor Detection on Social Media with Event Augmentations. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (Virtual Event, Canada) (SIGIR ’21) . Association for Computing Machinery, New York, NY, USA, 2020–2024
Zhenyu He, Ce Li, Fan Zhou, and Yi Yang. 2021 · 2024
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User Preference-Aware Fake News Detection. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (Virtual Event, Canada) (SIGIR ’21) . Association for Computing Machinery, New York, NY, USA, 2051–2055
Yingtong Dou, Kai Shu, Congying Xia, Philip S. Yu, and Lichao Sun. 2021 · 2055
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