Fnu Aryan

SymAnt merges a scene graph and a knowledge graph into one joint graph and uses the symbolic context found by graph search as the starting point for iterative decoding, so it can predict long action sequences from very short observation windows. In the short-observation settings of Breakfast and 50 Salads, its mean accuracy over classes exceeds the neuro-symbolic baseline NeSCA and several large-model baselines; on EPIC-KITCHENS, the 3M-parameter model performs comparably to fine-tuned models with billions of parameters. Because predictions are anchored in an editable graph, users can add or remove nodes at inference time to change predictions without retraining.

SymAnt merges a scene graph and a knowledge graph into one joint graph and uses the symbolic context found by graph search as the starting point for iterative decoding, so it can predict long action sequences from very short observation windows. In the short-observation settings of Breakfast and 50 Salads, its mean accuracy over classes exceeds the neuro-symbolic baseline NeSCA and several large-model baselines; on EPIC-KITCHENS, the 3M-parameter model performs comparably to fine-tuned models with billions of parameters. Because predictions are anchored in an editable graph, users can add or remove nodes at inference time to change predictions without retraining.