MV-Thinker: Multi-View Thinking with Adaptive Generation for Generative Recommendation
_reachsumit · x · 2026-11-04
A new arXiv paper proposes MV-Thinker, a 'Think Globally, Generate Personally' framework for semantic-ID-based generative recommendation.
- Multi-View Temporal Thinking: instead of mixing full-history and recent behaviors in one sequence (which dilutes current cues) or processing them separately, it uses view-specific thinking queries and readers to coordinate both into complementary user-conditioned representations.
- Adaptive Generation: lightweight residual adapters personalize decoder states at each step of autoregressive SID prediction, replacing the shared output-side transformation used by prior models.
The work targets two long-standing weaknesses of SID generative recommenders and comes from a team including Xiangyu Zhao's group.
More from Research
- François Chollet: modeling brain wiring as an engineering problem constrained by genome size and time — CatAstro_Piyush · 2026-11-04
- OffsecCyber dataset combines HackerOne reports and CVEs to train pentesting LLMs — AccBalanced · 2026-11-04
- Monofact rate in training data governs LLM scientific discovery, preprint finds — CatAstro_Piyush · 2026-11-04
- qwenTPU compiles a TPU into Qwen3.5 weights, achieving exact integer matmul — CatAstro_Piyush · 2026-11-04
- Jev model improves ICL demonstration retrieval via distillation into a lightweight MLP — kalyan_kpl · 2026-11-04
- Indie researcher open-sources 10 years of math work: 146k files, AI-accelerated over 3 years — HamOnWhy · 2026-11-04