·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Amazon’s search bar will invent AI-generated products you can’t buy1h◆Amazon will show AI product images when you search for some reason1h◆These two founders left Goldman and Meta to build voice AI for markets everyone else overlooked2h◆Publishers will be able to opt out of AI Search, thanks to new regulation2h◆Microsoft and OpenAI broke up — now they’re ready to fight3h◆Meta’s AI agent for WhatsApp Business is now available globally3h◆Coralogix raises $200M on bet that someone needs to watch the AI agents4h◆5 ways Google Search can level up your thrift and vintage shopping4h◆Direct Preference Optimization Beyond Chatbots4h◆AI has a water problem — Google thinks it has a fix8h◆Google must let publishers opt out of AI Search features, rules UK8h◆FederatedSkill: Federated Learning for Agentic Skill Evolution13h◆Toward a Modular Architecture for Embedded AI Agent Systems at the Edge13h◆A Graph Foundation Model with Spectral Parsing and Prototype-Guided Spatial Propagation13h◆Anomalies in Multivariate Time Series Benchmarks Are Mostly Univariate13h◆Evaluating the Reversal Curse in Model Editing13h◆Fast Unlearning at Scale via Margin Self-Correction13h◆Can Local Learning Match Self-Supervised Backpropagation?13h◆CAPER: Clause-Aligned Process Supervision for Text-to-SQL13h◆An Asymptotic Theory of Chain-of-Thought in In-Context Learning13h◆Amazon’s search bar will invent AI-generated products you can’t buy1h◆Amazon will show AI product images when you search for some reason1h◆These two founders left Goldman and Meta to build voice AI for markets everyone else overlooked2h◆Publishers will be able to opt out of AI Search, thanks to new regulation2h◆Microsoft and OpenAI broke up — now they’re ready to fight3h◆Meta’s AI agent for WhatsApp Business is now available globally3h◆Coralogix raises $200M on bet that someone needs to watch the AI agents4h◆5 ways Google Search can level up your thrift and vintage shopping4h◆Direct Preference Optimization Beyond Chatbots4h◆AI has a water problem — Google thinks it has a fix8h◆Google must let publishers opt out of AI Search features, rules UK8h◆FederatedSkill: Federated Learning for Agentic Skill Evolution13h◆Toward a Modular Architecture for Embedded AI Agent Systems at the Edge13h◆A Graph Foundation Model with Spectral Parsing and Prototype-Guided Spatial Propagation13h◆Anomalies in Multivariate Time Series Benchmarks Are Mostly Univariate13h◆Evaluating the Reversal Curse in Model Editing13h◆Fast Unlearning at Scale via Margin Self-Correction13h◆Can Local Learning Match Self-Supervised Backpropagation?13h◆CAPER: Clause-Aligned Process Supervision for Text-to-SQL13h◆An Asymptotic Theory of Chain-of-Thought in In-Context Learning13h◆
News/The Best of the Two Worlds: Harmonizing Semantic and Hash IDs for Sequential Recommendation
arxiv
PublishedMay 29, 2026 at 4:00 AM
—neutral

The Best of the Two Worlds: Harmonizing Semantic and Hash IDs for Sequential Recommendation

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

arXiv:2512.10388v2 Announce Type: replace-cross Abstract: Conventional Sequential Recommender Systems (SRS) typically assign unique hash IDs (HID) to construct item embeddings, which mainly capture collaborative signals from historical user-item interactions. However, such embeddings are vulnerable

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

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

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
03
#recommendation-systems#information-retrieval#artificial-intelligence

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →
Tags
03
#recommendation-systems#information-retrieval#artificial-intelligence

Related coverage

More from ARXIV
arxivFederatedSkill: Federated Learning for Agentic Skill Evolution13harxivToward a Modular Architecture for Embedded AI Agent Systems at the Edge13harxivA Graph Foundation Model with Spectral Parsing and Prototype-Guided Spatial Propagation13harxivAnomalies in Multivariate Time Series Benchmarks Are Mostly Univariate13h
The Bubble Brief
WEEKLY

Read recommendation-systems insights every Tuesday — top movers, new releases, story of the week.

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

Originally published on arxiv ↗
HomeModelsNews