Beyond Memorization: The Challenge of Random Memory Access in Language Models (2024.acl-long)
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| Challenge: | Recent advances in Language Models (LMs) have shown their effectiveness in knowledge-intensive tasks. |
| Approach: | They investigate whether a generative language model is able to access its memory sequentially or randomly. |
| Outcome: | The proposed LMs are able to access memory sequentially or randomly. |
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Unsupervised Natural Question Answering with a Small Model (D19-66)
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| Challenge: | a recent demonstration of the power of huge language models such as GPT-2 to memorise the answers to factoid questions raises questions about the extent to which knowledge is embedded directly within these large models. |
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