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guyulongcs/Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising

Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Pre-Ranking, Ranking (CTR/CVR prediction), Post Ranking, Relevance, LLM, Reinforcement Learning and so on.

2.4k 286 +0/wk
GitHub
advertising ctr cvr deep-learning recommender-system reinforcement-learning search search-engine
Trend 3

Star & Fork Trend (51 data points)

Stars
Forks

Multi-Source Signals

Growth Velocity

guyulongcs/Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising has +0 stars this period . 7-day velocity: 0.1%.

Deep analysis is being generated for this repository.

Signal-backed technical analysis will be available soon.

Metric Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising darknet_ros torchmetrics hyperlearn
Stars 2.4k 2.4k2.4k2.4k
Forks 286 1.2k484157
Weekly Growth +0 +0+0+1
Language Python C++PythonJupyter Notebook
Sources 1 111
License N/A BSD-3-ClauseApache-2.0Apache-2.0

Capability Radar vs darknet_ros

Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising
darknet_ros
Maintenance Activity 100

Last code push 4 days ago.

Community Engagement 59

Fork-to-star ratio: 11.8%. Active community forking and contributing.

Issue Burden 70

Issue data not yet available.

Growth Momentum 30

No measurable growth in the current period (first-day cold start expected).

License Clarity 30

No clear license detected — proceed with caution.

Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.