LLM4Delay uses large language models for flight delay prediction

By PulseAugur Editorial · [1 sources] · 2026-07-08 04:00

Researchers have developed LLM4Delay, a novel framework that utilizes large language models (LLMs) to predict flight delays. This model integrates textual aeronautical data, such as flight information and weather reports, with aircraft trajectory representations. By adapting trajectory data into a language modality, LLM4Delay aims to improve prediction accuracy and offers continuous updates as new information becomes available, showing potential for operational use in air traffic management. AI

IMPACT This research could enhance the efficiency of air traffic management systems through improved delay prediction.

RANK_REASON The cluster contains an academic paper detailing a new model and methodology. [lever_c_demoted from research: ic=1 ai=1.0]

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LLM4Delay uses large language models for flight delay prediction

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arXiv cs.AI TIER_1 English(EN) · Thaweerath Phisannupawong, Joshua Julian Damanik, Han-Lim Choi · 2026-07-08 04:00

LLM4Delay: Flight Delay Prediction via Cross-Modality Adaptation of Large Language Models and Aircraft Trajectory Representation

arXiv:2510.23636v4 Announce Type: replace-cross Abstract: Flight delay prediction has become a key focus in air traffic management (ATM), as delays reflect inefficiencies in the system. This paper proposes LLM4Delay, a large language model (LLM)-based framework for predicting fli…

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LLM4Delay: Flight Delay Prediction via Cross-Modality Adaptation of Large Language Models and Aircraft Trajectory Representation

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