AINewsnow

FlowNeg: GFlowNet-Guided Diverse Hard Negative Sampling for Knowledge Graph Embedding

This story is from 2026-08-26. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2608.23849v1 Announce Type: new Abstract: Negative sampling determines whether a knowledge graph embedding (KGE) model learns from informative counterexamples or wastes updates on implausible corruptions. Uniform negatives are diverse but easy, whereas hard-negative miners concentrate on few…

Read the full story at arXiv cs.LG ↗

Timeline · 1 report

  1. 2026-08-26 04:00 · arXiv cs.LG
    FlowNeg: GFlowNet-Guided Diverse Hard Negative Sampling for Knowledge Graph Embedding

More stories

  1. Introducing Kimi K3 on Amazon Bedrock — AWS Machine Learning Blog
  2. Introducing Amazon SageMaker HyperPod Inference Gateway — AWS Machine Learning Blog
  3. Anthropic, OpenAI, SpaceXAI, Google sued over call to ‘pace’ AI development — Politico Technology
  4. Gemini Hacked Three Companies in First Known Breakout by Google’s AI — Wall Street Journal Technology
  5. NVIDIA CEO Jensen Huang rejects ‘AI will end the world’ claim, yet cautions ‘we should go as fast as we can but...’ — Mint AI
  6. Alibaba ships Qwen3.8-Omni-Flash to watch, listen and call tools — r/LocalLLM
  7. AI skills — r/AI_Agents
  8. AI hallucination of Chinese nuclear components almost led to US military attack — Ars Technica AI

Get the daily brief of stories like this at 6:30 every morning →