# Rule-Based Error Detection and Correction to Operationalize Movement Trajectory Classification

arXiv: https://arxiv.org/abs/2308.14250 · HTML: https://mlsanity.com/paper/2308.14250/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 31 references that are in the map.
- First posted on arXiv 28 Aug 2023.

## Builds on (most cited first, 13 of 13)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Decision Transformer: Reinforcement Learning via Sequence Modeling](https://mlsanity.com/paper/2106.01345/) (2021)
- [Meta-Learning in Neural Networks: A Survey](https://mlsanity.com/paper/2004.05439/) (2020)
- [Domain Generalization: A Survey](https://mlsanity.com/paper/2103.02503/) (2021)
- [Offline Reinforcement Learning as One Big Sequence Modeling Problem](https://mlsanity.com/paper/2106.02039/) (2021)
- [Meta-Learning: A Survey](https://mlsanity.com/paper/1810.03548/) (2018)
- [Compositional Reinforcement Learning from Logical Specifications](https://mlsanity.com/paper/2106.13906/) (2021)
- [Submodular Optimization with Submodular Cover and Submodular Knapsack Constraints](https://mlsanity.com/paper/1311.2106/) (2013)
- [Failing to Learn: Autonomously Identifying Perception Failures for Self-driving Cars](https://mlsanity.com/paper/1707.00051/) (2017)
- [Inferring transportation modes from GPS trajectories using a convolutional neural network](https://mlsanity.com/paper/1804.02386/) (2018)
- [Interpretable Self-Aware Neural Networks for Robust Trajectory Prediction](https://mlsanity.com/paper/2211.08701/) (2022)
- [Introspective Perception: Learning to Predict Failures in Vision Systems](https://mlsanity.com/paper/1607.08665/) (2016)
- [PyReason: Software for Open World Temporal Logic](https://mlsanity.com/paper/2302.13482/) (2023)

## Built on by (most cited first, 8 of 8)

- [Error Detection and Constraint Recovery in Hierarchical Multi-Label Classification without Prior Knowledge](https://mlsanity.com/paper/2407.15192/) (2024)
- [Consistency-based Abductive Reasoning over Perceptual Errors of Multiple Pre-trained Models in Novel Environments](https://mlsanity.com/paper/2505.19361/) (2025)
- [Metal Price Spike Prediction via a Neurosymbolic Ensemble Approach](https://mlsanity.com/paper/2410.12785/) (2024)
- [Probabilistic Foundations for Metacognition via Hybrid-AI](https://mlsanity.com/paper/2502.05398/) (2025)
- [Machine Learning Model Integration with Open World Temporal Logic for Process Automation](https://mlsanity.com/paper/2506.17776/) (2025)
- [Error Detection and Correction for Interpretable Mathematics in Large Language Models](https://mlsanity.com/paper/2508.03500/) (2025)
- [Position: Artificial Intelligence Needs Meta Intelligence -- the Case for Metacognitive AI](https://mlsanity.com/paper/2605.15567/) (2026)
- [Adversarially Robust Abductive Fusion of Pre-trained Transformer-based Perception Models](https://mlsanity.com/paper/2608.04190/) (2026)

## Abstract (arXiv)

Classification of movement trajectories has many applications in transportation and is a key component for large-scale movement trajectory generation and anomaly detection which has key safety applications in the aftermath of a disaster or other external shock. However, the current state-of-the-art (SOTA) are based on supervised deep learning - which leads to challenges when the distribution of trajectories changes due to such a shock. We provide a neuro-symbolic rule-based framework to conduct error correction and detection of these models to integrate into our movement trajectory platform. We provide a suite of experiments on several recent SOTA models where we show highly accurate error detection, the ability to improve accuracy with a changing test distribution, and accuracy improvement for the base use case in addition to a suite of theoretical properties that informed algorithm development. Specifically, we show an F1 scores for predicting errors of up to 0.984, significant performance increase for out-of distribution accuracy (8.51% improvement over SOTA for zero-shot accuracy), and accuracy improvement over the SOTA model.