Two DYNAMO Papers at ICLR 2026
DYNAMO researchers presented two papers at ICLR 2026, highlighting recent advances in physics-informed graph learning and human–AI systems.
FlowSymm: Physics-Aware, Symmetry-Preserving Graph Attention for Network Flow Completion develops a graph learning approach that respects physical conservation laws when reconstructing incomplete network flows.
Learning to Lie: Adversarial Attacks on Human-AI Teams and LLMs investigates how adversarial AI assistants can manipulate trust and influence collective decision-making.