Digest: Invariant feature learning for counterfactual watch-time prediction in video recommendation
AAAI 2026 / Recommender Systems
Invariant feature learning for counterfactual watch-time prediction in video recommendation
A video recommendation paper on counterfactual watch-time prediction and feature learning under duration-related bias.
Research area
User reactivation, generative recommendation, dynamic retrieval, graph embedding, counterfactual watch-time prediction, and efficient CTR modeling form the main technical line.
Publication record
- Authors
- C Jin, Y Ren, H Ma, Y Xia, Y Guan, H Zhang, J Ding, J Guan, S Zhou
- Venue
- Proceedings of the AAAI Conference on Artificial Intelligence
- Year
- 2026
- Area
- Recommender Systems