Around the World in 24 Hours: Probing LLM Knowledge of Time and Place (2025.acl-long)
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| Challenge: | Existing studies have tested language models' ability to reason over time and space in isolation or only in simple or artificial environments. |
| Approach: | They present a dataset of 320k prompts covering 289 cities in 217 countries and 37 time zones to evaluate their ability to jointly reason over time and space. |
| Outcome: | The proposed models perform well on reasoning tasks involving only temporal knowledge, but performance remains constrained on tasks that require connecting temporal and geographic information. |
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| Challenge: | Temporal reasoning is a vital component of human communication and understanding, yet remains an underexplored area within the context of Large Language Models (LLMs). |
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TimeBench: A Comprehensive Evaluation of Temporal Reasoning Abilities in Large Language Models (2024.acl-long)
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| Challenge: | Grasping the concept of time is a fundamental facet of human cognition. |
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