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We present Palm, a solution to the Long-Term Action Anticipation (LTA) taskutilizing vision-language and large language models. Given an input video withannotated action periods, the LTA task aims to predict possible future actions.We hypothesize that an optimal solution should capture the interdependencybetween past and future actions, and be able to infer future actions based onthe structure and dependency encoded in the past actions. Large language modelshave demonstrated remarkable commonsense-based reasoning ability. Inspired bythat, Palm chains an image captioning model and a large language model. Itpredicts future actions based on frame descriptions and action labels extractedfrom the input videos. Our method outperforms other participants in the EGO4DLTA challenge and achieves the best performance in terms of action prediction.Our code is available at https://github.com/DanDoge/Palm

Palm: Predicting Actions through Language Models @ Ego4D Long-Term Action Anticipation Challenge 2023