3 accepted papers
Ride-hailing platforms face the challenge of balancing passenger waiting times with overall system efficiency under highly uncertain supply–demand conditions. Adaptive delayed matching, which controls the holding intervals for batched sets of requests and vehicles, reveals an inherent trade-off betw…
Various parameter-efficient fine-tuning (PEFT) methods, including LoRA and its variants, have gained popularity for reducing computational costs. However, there is often an accuracy gap between PEFT approaches and full fine-tuning (FT), and this discrepancy has not yet been systematically explored.…
The over-smoothing issue is a well-known challenge for Graph Convolutional Networks (GCN). Specifically, it is often observed that increasing the depth of GCN ends up in a trivial embedding subspace where the difference among node embeddings belonging to the same cluster tends to vanish. This paper…