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Found 6 papers, 2 papers with code
On the Planning Abilities of Large Language Models (A Critical Investigation with a Proposed Benchmark)
On this benchmark, we evaluate LLMs in three modes: autonomous, heuristic and human-in-the-loop.
PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change
PlanBench provides sufficient diversity in both the task domains and the specific planning capabilities.
GPT3-to-plan: Extracting plans from text using GPT-3
Operations in many essential industries including finance and banking are often characterized by the need to perform repetitive sequential tasks.
Not all Failure Modes are Created Equal: Training Deep Neural Networks for Explicable (Mis)Classification
classifying the image of a dog to an airplane) can perplex humans and result in the loss of human trust in the system.
Imperfect ImaGANation: Implications of GANs Exacerbating Biases on Facial Data Augmentation and Snapchat Selfie Lenses
In this paper, we show that popular Generative Adversarial Networks (GANs) exacerbate biases along the axes of gender and skin tone when given a skewed distribution of face-shots.
Model-Free Model Reconciliation
One such approach has been the idea of {\em explanation as model-reconciliation}.
