most citedUnlocking Temporal Question Answering for Large Language Models with Tailor-Made Reasoning Logic

5 citations · 5 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CL2023

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…

cs.CL2023★ 5 cited

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…