Row 5267

Row ID: 5267 | Dataset Entry | Axioma AXP Content Repository

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[https://arxiv.org/abs/2404.15758](https://arxiv.org/abs/2404.15758)

# From the abstract

We show that transformers can use meaningless filler tokens (e.g., '......') in place of a chain of thought to solve two hard algorithmic tasks they could not solve when responding without intermediate tokens. However, we find empirically that learning to use filler tokens is difficult and requires specific, dense supervision to converge

FieldValue
text [https://arxiv.org/abs/2404.15758](https://arxiv.org/abs/2404.15758) # From the abstract We show that transformers can use meaningless filler tokens (e.g., '......') in place of a chain of thought to solve two hard algorithmic tasks they could not solve when responding without intermediate tokens. However, we find empirically that learning to use filler tokens is difficult and requires specific, dense supervision to converge
label r/machinelearning
dataType post
communityName r/MachineLearning
datetime 2024-04-28
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Raw Record

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  "text": "[https://arxiv.org/abs/2404.15758](https://arxiv.org/abs/2404.15758)\n\n# From the abstract\n\n  \nWe show that transformers can use meaningless filler tokens (e.g., '......') in place of a chain of thought to solve two hard algorithmic tasks they could not solve when responding without intermediate tokens. However, we find empirically that learning to use filler tokens is difficult and requires specific, dense supervision to converge",
  "label": "r/machinelearning",
  "dataType": "post",
  "communityName": "r/MachineLearning",
  "datetime": "2024-04-28",
  "username_encoded": "Z0FBQUFBQm5LakwyV1U5OFppTmRmTmRUTEU5MGkzNGlVT3B5dVhMeS1TWFlzaUQ4S1VscVBSV0xxSUVXaEd2Q21aS1lTSXcwUldxLVJSVE8xSmRUVlNFdFlkeEJCZ3V3TE16U0I0OEw4aVBCdU5KZVNUbm1hUFk9",
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}
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