Zhengbao Jiang
5 أوراق في مجموعة PaperMetrix
أوراق هذا المؤلف
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How Can We Know When Language Models Know? On the Calibration of Language Models for Question Answering
2020 · arXiv (Cornell University)
Recent works have shown that language models (LM) capture different types of knowledge regarding facts or common sense. However, because no model is perfect, they still fail to provide appropriate answers in many cases. In …
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Beyond Memorization: The Challenge of Random Memory Access in Language Models
2024
Recent developments in Language Models (LMs) have shown their effectiveness in NLP tasks, particularly in knowledge-intensive tasks.However, the mechanisms underlying knowledge storage and memory access within their parameters remain elusive.In this paper, we investigate whether …
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Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
2022 · ACM Computing Surveys
This article surveys and organizes research works in a new paradigm in natural language processing, which we dub “prompt-based learning.” Unlike traditional supervised learning, which trains a model to take in an input x and …
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Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
2021 · arXiv (Cornell University)
This paper surveys and organizes research works in a new paradigm in natural language processing, which we dub "prompt-based learning". Unlike traditional supervised learning, which trains a model to take in an input x and …
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Active Retrieval Augmented Generation
2023
Zhengbao Jiang, Frank Xu, Luyu Gao, Zhiqing Sun, Qian Liu, Jane Dwivedi-Yu, Yiming Yang, Jamie Callan, Graham Neubig. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. 2023.