2 papers
cs.AI2026
When Agents Coordinate: Measuring Coordination in Multi-Agent AI Coding
Giuseppe Destefanis, Tomaso Aste
We study how teams of AI coding agents coordinate while solving programming tasks. Current evaluations usually report whether the agents complete the task and how much the run cost…
q-fin.ST2026
Dependence-Informed Sparse Neural Architecture for Stock Return Prediction
Hongyu Lin, Yulin Chen, Yuanrong Wang +2
Using neural networks for stock return prediction typically requires choices about depth and hidden-layer width that are difficult to connect to financial interpretation. We study…