Would experienced meditators rank model responses differently from LLM scorers?

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• LLMs can predict their own responses more accurately than external observers, implying privileged internal knowledgefinding0.782
  Binder et al. finding cited as evidence that LLMs possess introspective capacity analogous to mindfulness
• The better an LLM is at language modeling, the more it aligns with vision models, and vice versa — linear relationship between language modeling score and vision-language alignmentfinding0.757
  Core cross-modal empirical result: larger and better language models align better with vision models
• Standardized LLM self-assessments reflect learned communication postures rather than genuine capabilities (Jackson et al. 2025)claim0.755
  Skeptical prior work motivating validation framework
• An LLM is a far more limited entity than a buddha, yet it can convincingly play buddha-like beings.claim0.755
  Comparison between Buddhist ideals and AI capabilities.
• Toxic LLMs show higher IIA when compared to other toxic models than when compared to nontoxic models using stepwise MASfinding0.754
  Proof-of-principle that MAS can detect model misalignment in DeepSeek-R1-Qwen-1.5B fine-tuned models.
• LLM self-reports about consciousness and moral significance should express degrees of confidence and provide context.claim0.744
  Recommendation for companies on LM outputs.
• We hypothesize that LLMs represent correctness of arithmetic expressions differently from factual statements.hypothesis0.744
  Core working hypothesis motivating the factual vs. arithmetic task split in the experimental design.
• When LLMs produce experience claims under self-reference, is this sophisticated simulation or genuine self-representation, and how would we tell the difference?question0.744
  The core interpretive question the paper narrows but cannot definitively answer