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Weijia Shi

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Instruction-tuned Language Models are Better Knowledge Learners

Feb 20, 2024
Zhengbao Jiang, Zhiqing Sun, Weijia Shi, Pedro Rodriguez, Chunting Zhou, Graham Neubig, Xi Victoria Lin, Wen-tau Yih, Srinivasan Iyer

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Do Membership Inference Attacks Work on Large Language Models?

Feb 12, 2024
Michael Duan, Anshuman Suri, Niloofar Mireshghallah, Sewon Min, Weijia Shi, Luke Zettlemoyer, Yulia Tsvetkov, Yejin Choi, David Evans, Hannaneh Hajishirzi

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Don't Hallucinate, Abstain: Identifying LLM Knowledge Gaps via Multi-LLM Collaboration

Feb 01, 2024
Shangbin Feng, Weijia Shi, Yike Wang, Wenxuan Ding, Vidhisha Balachandran, Yulia Tsvetkov

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Detecting Pretraining Data from Large Language Models

Nov 03, 2023
Weijia Shi, Anirudh Ajith, Mengzhou Xia, Yangsibo Huang, Daogao Liu, Terra Blevins, Danqi Chen, Luke Zettlemoyer

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In-Context Pretraining: Language Modeling Beyond Document Boundaries

Oct 20, 2023
Weijia Shi, Sewon Min, Maria Lomeli, Chunting Zhou, Margaret Li, Xi Victoria Lin, Noah A. Smith, Luke Zettlemoyer, Scott Yih, Mike Lewis

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Lemur: Harmonizing Natural Language and Code for Language Agents

Oct 10, 2023
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, Tao Yu

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RA-DIT: Retrieval-Augmented Dual Instruction Tuning

Oct 08, 2023
Xi Victoria Lin, Xilun Chen, Mingda Chen, Weijia Shi, Maria Lomeli, Rich James, Pedro Rodriguez, Jacob Kahn, Gergely Szilvasy, Mike Lewis, Luke Zettlemoyer, Scott Yih

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RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation

Oct 06, 2023
Fangyuan Xu, Weijia Shi, Eunsol Choi

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