Few-step and hardware-aware sampling for X-Rec

Develop few-step distillation, adaptive numerical solvers, and hardware-aware optimization for the X-Rec sampler to reduce the end-to-end serving costs caused by its multiple denoising steps.

Background

X-Rec generates continuous item-embedding retrieval triggers through Riemannian flow matching and currently requires multiple denoising steps during inference. Although this design provides expressive retrieval distributions, repeated numerical integration increases serving cost. The paper identifies reducing this cost through few-step distillation, adaptive solvers, and hardware-aware optimization as an unresolved future direction.

References

Several directions remain open for future work. First, the current sampler requires multiple denoising steps, motivating the exploration of few-step distillation, adaptive numerical solvers, and hardware-aware optimization to reduce end-to-end serving costs.

— X-Rec Technical Report  (2609.29180 - Shen et al., 24 Sep 2026) in Section Conclusion and Future Work

Second, although the late-interaction design is computationally efficient, its scalability remains to be fully explored. Under strict serving-throughput constraints, practical systems must balance retrieval quality against generation cost. Future work could investigate how late interaction scales with larger backbones and deeper denoising modules, as well as adaptive computation mechanisms that dynamically balance quality and efficiency.

— X-Rec Technical Report  (2609.29180 - Shen et al., 24 Sep 2026) in Section Conclusion and Future Work