Papers by Graham Todd

2 papers
ByteSized32: A Corpus and Challenge Task for Generating Task-Specific World Models Expressed as Text Games (2023.emnlp-main)

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Challenge: We show that language models can generate explicit, interpretable, and interactive world models of scientific and common-sense reasoning tasks.
Approach: They propose a corpus of 32 reasoning-focused text games expressed as hundreds of lines of Python code to facilitate this task.
Outcome: The proposed games can generate runnable games on unseen topics in 28% of cases.
Can Language Models Serve as Text-Based World Simulators? (2024.acl-short)

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Challenge: Recent advances in large language models (LLMs) have pointed towards an alternative approach by leveraging the huge amount of knowledge contained in their pre-training datasets.
Approach: They build and use a benchmark to quantify how well text-based simulators can serve as text-driven world simulators.
Outcome: The proposed benchmark aims to quantify how well language models can serve as world simulators.

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