Unverified50% confidenceOpinionExact time
Astra appeared to read the weights natively in the MIT experiment because the researchers pasted the 17,253 weights into the prompt as plain text, and the model only needed to do pattern matching within the token sequence; for a real network with millions of parameters, serializing everything into the context is neither realistic nor economical.
1
Sources
50%
Confidence
Long-term
Relevance
11/4/2026
First Seen
Sources
Can Qwen 3.8 27B Really Read Neural Network Weights? A 16GB Hands-On Test
youtubeOpaya11/4/2026
Related Entities
Related Claims
UnverifiedIn the test, the payload was passed word-for-word to the reading model with only each vendor's built-in synthesis functionality removed, and token counts were derived from actual bills rather than estimates.62% similarUnverifiedA Reddit developer encoded the weights of a 17,253-parameter neural network as a sequence of plain-text tokens and fed them into a language model, which determined that the network was used to play Pac-Man.61% similarUnverifiedThe Bayesian precision calculator script in the article hardcodes a single set of values, has no input interface, and does not handle multi-class scenarios.60% similarUnverifiedStatic reading is almost ineffective against control flow flattening; readable form can only be restored through dynamic execution or with the help of AST restoration tools.60% similarUnverifiedThe experiment used only one rewriter, one prompt, one seed per setting, and only 100 texts per setting, the flagged-rate confidence intervals are wide, and the Ollama models are 4-bit quantized.59% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1135726API
curl https://kongchang.com/api/v1/knowledge/claims/1135726MCP
get_claim(id=1135726)