TasteRoute: Personalized Routing for Video Generation

📅 2026-10-05
📈 Citations: 0
✨ Influential: 0
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🤖 AI Summary
This study addresses the challenge of aligning video generation models—whose capabilities and costs vary significantly—with personalized user demands. To this end, we propose a cost-aware personalized video generation router that jointly models textual prompts, subjective user preferences, and budget constraints. By leveraging multi-model comparisons and human preference annotations, the routing algorithm achieves an optimal trade-off between generation quality and economic cost. Furthermore, we release a high-quality dataset annotated with user preferences. Experimental results demonstrate that the proposed router is competitive in preference alignment tasks while substantially reducing average generation costs, exhibiting particularly pronounced advantages under strict budget constraints.
📝 Abstract
Rapid progress in video generation has led to a plethora of models that differ substantially in capability and generation cost. This raises a natural question: can each request be efficiently routed to an appropriate model? We find that even when the consensus of the other annotators is used as an oracle, it agrees with each annotator's own favorite only 34-55% of the time. Motivated by this observation, we introduce TasteRoute, a personalized video-generation router that selects a generator jointly based on the input request, user preferences, and available generation budget. Across text-to-video and image-to-video settings, TasteRoute is competitive with strong simple baselines on preference routing while reducing average generation cost. The cost saving increases under higher budget caps. Finally, we release TasteRoute-3k, a human-annotated dataset containing multi-model video comparisons, quality judgments, preference rankings, and user-profile signals to facilitate future research on personalized and cost-aware video routing.
Problem

Research questions and friction points this paper is trying to address.

Video Generation
Personalized Routing
User Preference
Cost-aware Routing
Innovation

Methods, ideas, or system contributions that make the work stand out.

Personalized Routing
Video Generation
Cost-aware
User Preference
TasteRoute-3k
Zhi Rui Tam
Zhi Rui Tam
NTU / Appier
natural language processing
C
Chao-Chung Wu
Appier Inc.
S
Sin-Han Yang
Appier Inc.
P
Peyton Ku
Appier Inc.
B
Brendan Kuang
Appier Inc.
T
Tzu-Ting Hsieh
Appier Inc.
M
Min-Fang Hsu
Appier Inc.
F
Fang-Ling Tsai
Appier Inc.
Y
Yun-Nung Chen
National Taiwan University
Wei-Chiu Ma
Wei-Chiu Ma
Assistant Professor, Cornell University
Computer VisionRoboticsMachine Learning
Chieh-Yen Lin
Chieh-Yen Lin
Appier AI Research
Artificial IntelligenceMachine Learning