LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation
Proposes a two-stage training framework that adapts LLMs to capture both semantic understanding and collaborative filtering signals.
📝 arxiv.org/abs/2506.21579
👨🏽💻 github.com/HappyPointer...
Proposes a two-stage training framework that adapts LLMs to capture both semantic understanding and collaborative filtering signals.
📝 arxiv.org/abs/2506.21579
👨🏽💻 github.com/HappyPointer...
LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation
Sequential recommendation aims to predict users' future interactions by modeling collaborative filtering (CF) signals from historical behaviors of similar users or items. Traditional sequential recomm...
arxiv.org
June 30, 2025 at 3:52 AM
LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation
Proposes a two-stage training framework that adapts LLMs to capture both semantic understanding and collaborative filtering signals.
📝 arxiv.org/abs/2506.21579
👨🏽💻 github.com/HappyPointer...
Proposes a two-stage training framework that adapts LLMs to capture both semantic understanding and collaborative filtering signals.
📝 arxiv.org/abs/2506.21579
👨🏽💻 github.com/HappyPointer...
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March 11, 2026 at 12:10 PM
Reasoning over Semantic IDs Enhances Generative Recommendation
Proposes a two-stage framework that enables LLMs to reason over discrete item tokens for generative recommendation, using enriched SID-language alignment and RL.
📝 arxiv.org/abs/2603.23183
👨🏽💻 github.com/HappyPointer...
Proposes a two-stage framework that enables LLMs to reason over discrete item tokens for generative recommendation, using enriched SID-language alignment and RL.
📝 arxiv.org/abs/2603.23183
👨🏽💻 github.com/HappyPointer...
Reasoning over Semantic IDs Enhances Generative Recommendation
Recent advances in generative recommendation have leveraged pretrained LLMs by formulating sequential recommendation as autoregressive generation over a unified token space comprising language tokens ...
arxiv.org
March 25, 2026 at 5:08 AM
Reasoning over Semantic IDs Enhances Generative Recommendation
Proposes a two-stage framework that enables LLMs to reason over discrete item tokens for generative recommendation, using enriched SID-language alignment and RL.
📝 arxiv.org/abs/2603.23183
👨🏽💻 github.com/HappyPointer...
Proposes a two-stage framework that enables LLMs to reason over discrete item tokens for generative recommendation, using enriched SID-language alignment and RL.
📝 arxiv.org/abs/2603.23183
👨🏽💻 github.com/HappyPointer...