Uncertainty is Fragile: Manipulating Uncertainty in Large Language Models

Algorithmic learning in a random world , volume 29

Vladimir Vovk, Alexander Gammerman, and Glenn Shafer · 2005

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Hotflip: White-box adversarial examples for text classification

Original

Javid Ebrahimi, Anyi Rao, Daniel Lowd, and Dejing Dou · 2017

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Simple and scalable predictive uncertainty estimation using deep ensembles

Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell · 2017

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Get to the point: Summarization with pointer-generator networks

Abigail See, Peter J. Liu, and Christopher D. Manning · 2017

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Trick me if you can: Human-in-the-loop generation of adversarial examples for question answering

Eric Wallace, Pedro Rodriguez, Shi Feng, Ikuya Yamada, and Jordan Boyd-Graber · 2019

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Quantifying uncertainties in natural language processing tasks

Yijun Xiao and William Yang Wang · 2019

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Badnets: Evaluating backdooring attacks on deep neural networks

Tianyu Gu, Kang Liu, Brendan Dolan-Gavitt, and Siddharth Garg · 2019

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Cosmos QA: Machine reading comprehension with contextual commonsense reasoning

Lifu Huang, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi · 2019

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HellaSwag: Can a machine really finish your sentence?

Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi · 2019

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Hidden trigger backdoor attacks

Aniruddha Saha, Akshayvarun Subramanya, and Hamed Pirsiavash · 2020

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Clean-label backdoor attacks on video recognition models

Shihao Zhao, Xingjun Ma, Xiang Zheng, James Bailey, Jingjing Chen, and Yu-Gang Jiang · 2020

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Measuring massive multitask language understanding

Original

Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt · 2020

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Gradient-based adversarial attacks against text transformers

Original

Chuan Guo, Alexandre Sablayrolles, Hervé Jégou, and Douwe Kiela · 2021

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Bot-adversarial dialogue for safe conversational agents

Jing Xu, Da Ju, Margaret Li, Y-Lan Boureau, Jason Weston, and Emily Dinan · 2021

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Lira: Learnable, imperceptible and robust backdoor attacks

Khoa Doan, Yingjie Lao, Weijie Zhao, and Ping Li · 2021

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How can we know when language models know? on the calibration of language models for question answering

Zhengbao Jiang, Jun Araki, Haibo Ding, and Graham Neubig · 2021

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Backdoor attacks on pre-trained models by layerwise weight poisoning

Original

Linyang Li, Demin Song, Xiaonan Li, Jiehang Zeng, Ruotian Ma, and Xipeng Qiu · 2021

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What disease does this patient have? a large-scale open domain question answering dataset from medical exams

Di Jin, Eileen Pan, Nassim Oufattole, Wei-Hung Weng, Hanyi Fang, and Peter Szolovits · 2021

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Lora: Low-rank adaptation of large language models

Edward J Hu, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen, et al · 2021

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ONION: A simple and effective defense against textual backdoor attacks

Fanchao Qi, Yangyi Chen, Mukai Li, Yuan Yao, Zhiyuan Liu, and Maosong Sun · 2021

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Expectation vs. experience: Evaluating the usability of code generation tools powered by large language models

Priyan Vaithilingam, Tianyi Zhang, and Elena L Glassman · 2022

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Language models (mostly) know what they know

Original

Saurav Kadavath, Tom Conerly, Amanda Askell, Tom Henighan, Dawn Drain, Ethan Perez, Nicholas Schiefer, Zac Hatfield-Dodds, Nova DasSarma, Eli Tran-Johnson, et al · 2022

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Audio-domain position-independent backdoor attack via unnoticeable triggers

Cong Shi, Tianfang Zhang, Zhuohang Li, Huy Phan, Tianming Zhao, Yan Wang, Jian Liu, Bo Yuan, and Yingying Chen · 2022

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Exploring the universal vulnerability of prompt-based learning paradigm

Original

Lei Xu, Yangyi Chen, Ganqu Cui, Hongcheng Gao, and Zhiyuan Liu · 2022

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Large language models are state-of-the-art evaluators of code generation

Original

Terry Yue Zhuo · 2023

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Nphardeval: Dynamic benchmark on reasoning ability of large language models via complexity classes

Original

Lizhou Fan, Wenyue Hua, Lingyao Li, Haoyang Ling, Yongfeng Zhang, and Libby Hemphill · 2023

Cited alongside, same era.

Llms for financial advisement: A fairness and efficacy study in personal decision making

Mistral 7b, 2023

Original

Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed · 2023

Later among the works it cites.

Chain-of-thought prompting elicits reasoning in large language models, 2023

Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, and Denny Zhou · 2023

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Large language models for mathematical reasoning: Progresses and challenges

Original

Janice Ahn, Rishu Verma, Renze Lou, Di Liu, Rui Zhang, and Wenpeng Yin · 2024

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Mathchat: Converse to tackle challenging math problems with llm agents

Yiran Wu, Feiran Jia, Shaokun Zhang, Hangyu Li, Erkang Zhu, Yue Wang, Yin Tat Lee, Richard Peng, Qingyun Wu, and Chi Wang · 2024

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Nphardeval4v: A dynamic reasoning benchmark of multimodal large language models