2 papers
cs.CL2024
Unlocking Temporal Question Answering for Large Language Models with Tailor-Made Reasoning Logic
Xingxuan Li, Liying Cheng, Qingyu Tan +3
The temporal aspect is a significant dimension of our reality. We notice the challenge that large language models (LLMs) face when engaging in temporal reasoning. Our preliminary e…
cs.CL2024
Towards Robust Temporal Reasoning of Large Language Models via a Multi-Hop QA Dataset and Pseudo-Instruction Tuning
Qingyu Tan, Hwee Tou Ng, Lidong Bing
Knowledge in the real world is being updated constantly. However, it is costly to frequently update large language models (LLMs). Therefore, it is crucial for LLMs to understand th…