KuaiLive is the first publicly released real-time interactive dataset for live streaming recommendation, with logs from 23,772 users and 452,621 streamers over 21 days plus timestamps, multi-type interactions, and side features.
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3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
representative citing papers
FLUID introduces LUCID semantic codes from a multimodal encoder to retire item IDs in livestreaming rankers, with staged warmup yielding online gains of +0.55% watch duration and +2.05% cold-start views.
SSRLive combines generative and discriminative modules with dynamic semantic IDs to improve live streaming recommendations, reporting gains of +3.38% watch time, +0.72% GMV, +3.12% follower growth, and +2.92% interaction volume in online A/B tests.
citing papers explorer
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KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendation
KuaiLive is the first publicly released real-time interactive dataset for live streaming recommendation, with logs from 23,772 users and 452,621 streamers over 21 days plus timestamps, multi-type interactions, and side features.
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FLUID: From Ephemeral IDs to Multimodal Semantic Codes for Industrial-Scale Livestreaming Recommendation
FLUID introduces LUCID semantic codes from a multimodal encoder to retire item IDs in livestreaming rankers, with staged warmup yielding online gains of +0.55% watch duration and +2.05% cold-start views.
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SSRLive: Live Streaming Recommendation with Dynamic Semantic ID
SSRLive combines generative and discriminative modules with dynamic semantic IDs to improve live streaming recommendations, reporting gains of +3.38% watch time, +0.72% GMV, +3.12% follower growth, and +2.92% interaction volume in online A/B tests.