Large Language Models (LLMs) have emerged as powerful tools for generating coherent text, understanding context, and performing reasoning tasks. However, they struggle with temporal reasoning, which requires processing time-related information such as event sequencing, durations, and inter-temporal relationships. These capabilities are critical for applications including question answering, scheduling, and historical analysis. In this paper, we introduce TISER, a novel framework that enhances the temporal reasoning abilities of LLMs through a multi-stage process that combines timeline construction with iterative self-reflection. Our approach leverages test-time scaling to extend the length of reasoning traces, enabling models to capture complex temporal dependencies more effectively. This strategy not only boosts reasoning accuracy but also improves the traceability of the inference process. Experimental results demonstrate state-of-the-art performance across multiple benchmarks, including out-of-distribution test sets, and reveal that TISER enables smaller open-source models to surpass larger closed-weight models on challenging temporal reasoning tasks.

The first female pilot to fly solo from Britain to Australia has been'brought back to life' with ground-breaking 3D technology. Amy Johnson completed the journey from London to Darwin in 1930 - one of many record-breaking flights during her career. To mark 75 years since her death, experts have created a fully interactive digital 3D version of Ms Johnson, which can even walk and talk about her achievements. The first female pilot to fly solo from Britain to Australia has been'brought back to life' with ground-breaking 3D technology. 'Virtual Amy' will go display in the children's library within Hull Central Library as part of the Amy Johnson Festival.