Cited by: Scaling Laws for Neural Language Models

42 citation edges inside this catalog. A title match is weaker evidence than an identifier match. Zero entries does not mean no citations on the web.

• TTRL: Test-Time Reinforcement Learning
  arxiv:2504.16084 · evidence: id
• The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning
  arxiv:2505.15134 · evidence: id
• How much do language models memorize?
  arxiv:2505.24832 · evidence: id
• Reinforcement Pre-Training
  arxiv:2506.08007 · evidence: title
• Mixture-of-Recursions: Learning Dynamic Recursive Depths for Adaptive Token-Level Computation
  arxiv:2507.10524 · evidence: id
• Less is More: Recursive Reasoning with Tiny Networks
  arxiv:2510.04871 · evidence: id
• NorMuon: Making Muon more efficient and scalable
  arxiv:2510.05491 · evidence: id
• The Art of Scaling Reinforcement Learning Compute for LLMs
  arxiv:2510.13786 · evidence: id
• Encoder-Decoder or Decoder-Only? Revisiting Encoder-Decoder Large Language Model
  arxiv:2510.26622 · evidence: id
• Continuous Autoregressive Language Models
  arxiv:2510.27688 · evidence: id
• Nested Learning: The Illusion of Deep Learning Architectures
  arxiv:2512.24695 · evidence: id
• Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering
  arxiv:2604.08224 · evidence: id
• Structured Scaling of AI Discovery Across Diverse Scientific Domains
  arxiv:2604.19341 · evidence: id
• Emergent Capabilities Arise Randomly from Learning Sparse Attention Patterns
  arxiv:2606.25010 · evidence: id
• A social path to human-like artificial intelligence
  doi:10.1038/s42256-023-00754-x · evidence: id
• Characterizing emergent phenomena in LLMs (Google Research)
  url:ai.googleblog.com/2022/11/characterizing-emergent-phenomena-in.html · evidence: id
• Mapping the mind of a large language model (Anthropic)
  url:anthropic.com/news/mapping-mind-language-model · evidence: id
• Deep Double Descent (OpenAI)
  url:openai.com/index/deep-double-descent · evidence: title