·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Figma announces new features to define how agents work on its platform5h◆Narrowing the Collaboration Gap, Probably6h◆Divide, Consult, Conquer: Capability Laundering Through Aligned LLMs6h◆ViTeX-Bench: Benchmarking High-Fidelity Video Scene Text Editing6h◆MoLE: Mixture of Latent Experts for Complementary Visual Reasoning6h◆Distribution Matching Evolutionary Algorithms for Rare Event Sampling6h◆Why Software Engineering Is Indispensable in the Age of Coding Agents6h◆NavGPT-3: Harnessing Context in a Hierarchical Navigation Runtime6h◆Structure-Preserving Document-Level Data Augmentation via Discourse Parsing6h◆One Block Ahead: Promoting Sampler State in Diffusion Language Models6h◆Recognizing Dialogue Ambiguity via Candidate Set Visual Grounding6h◆AFCS: Atomic-Fact-Conditioned Synthesis for Factual Knowledge Pretraining6h◆Beyond Aggregate Accuracy: Item-Level Transitions in Prompt Optimization6h◆Function-Space Temporal Self-Distillation for Policy Optimization6h◆Scaling Cheap Synthetic Pretraining Improves Indoor Radio-Map Prediction6h◆AVA-Encoder: Towards Agent-Native Video Representation Learning6h◆TRACER: Trace-Regularized Training Against Indirect Prompt Injection6h◆Towards Training and Inference of Graph Neural Networks in Graph Databases6h◆CAST: History-Adaptive Spectral Clipping for LLM Pretraining6h◆Beyond DFT electronic band structures via dual-space orbital learning6h◆Figma announces new features to define how agents work on its platform5h◆Narrowing the Collaboration Gap, Probably6h◆Divide, Consult, Conquer: Capability Laundering Through Aligned LLMs6h◆ViTeX-Bench: Benchmarking High-Fidelity Video Scene Text Editing6h◆MoLE: Mixture of Latent Experts for Complementary Visual Reasoning6h◆Distribution Matching Evolutionary Algorithms for Rare Event Sampling6h◆Why Software Engineering Is Indispensable in the Age of Coding Agents6h◆NavGPT-3: Harnessing Context in a Hierarchical Navigation Runtime6h◆Structure-Preserving Document-Level Data Augmentation via Discourse Parsing6h◆One Block Ahead: Promoting Sampler State in Diffusion Language Models6h◆Recognizing Dialogue Ambiguity via Candidate Set Visual Grounding6h◆AFCS: Atomic-Fact-Conditioned Synthesis for Factual Knowledge Pretraining6h◆Beyond Aggregate Accuracy: Item-Level Transitions in Prompt Optimization6h◆Function-Space Temporal Self-Distillation for Policy Optimization6h◆Scaling Cheap Synthetic Pretraining Improves Indoor Radio-Map Prediction6h◆AVA-Encoder: Towards Agent-Native Video Representation Learning6h◆TRACER: Trace-Regularized Training Against Indirect Prompt Injection6h◆Towards Training and Inference of Graph Neural Networks in Graph Databases6h◆CAST: History-Adaptive Spectral Clipping for LLM Pretraining6h◆Beyond DFT electronic band structures via dual-space orbital learning6h◆
News/Unleash LLMs Potential for Sequential Recommendation by Coordinating Dual Dynamic Index Mechanism
arxiv
PublishedSeptember 17, 2026 at 4:00 AM
—neutral

Unleash LLMs Potential for Sequential Recommendation by Coordinating Dual Dynamic Index Mechanism

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2409.09253v2 Announce Type: replace-cross Abstract: Owing to the unprecedented capability in semantic understanding and logical reasoning, large language models (LLMs) have shown fantastic potential in developing next-generation sequential recommender systems (RSs). However, existing LLM-based

Stay posted· Newsletter

Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.

// no spam · unsubscribe one-click · free forever

Your email is used only to send The Bubble Brief. Privacy policy

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivNarrowing the Collaboration Gap, Probably6harxivDivide, Consult, Conquer: Capability Laundering Through Aligned LLMs6harxivViTeX-Bench: Benchmarking High-Fidelity Video Scene Text Editing6harxivMoLE: Mixture of Latent Experts for Complementary Visual Reasoning6h
The Bubble Brief
MON · WED · FRI

Read AI insights every Monday, Wednesday and Friday — top movers, new models, story of the week.

// no spam · unsubscribe one-click · free forever

Your email is used only to send The Bubble Brief. Privacy policy

Originally published on arxiv ↗
PrivacyTermsRefundsLegal notice|AboutMethodologyContact

© 2026 Databubble

Built by Marouane Gazouzi · Readyo, AI interview coach

HomeModelsNews