Unverified50% confidenceFactExact time
Using step functions or hard-threshold activation functions to simulate logic gates faces the problems of vanishing gradients or non-differentiability, making training via backpropagation difficult.
1
Sources
50%
Confidence
Long-term
Relevance
11/3/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedSimply increasing model scale or extending training duration does not automatically solve the problem of hard tasks being neglected, because the root cause lies in the absence of the signal itself.74% similarUnverified简单堆砌上下文长度并不能线性提升长任务性能,因存在中间丢失问题72% similarUnverifiedAs long as chunked compression is done by fixed length, the phase sensitivity problem cannot be avoided; this is a structural flaw of the scheme itself and cannot be eradicated by tuning parameters, changing positional encoding or post-training.70% similarUnverifiedHarmonic extension fills in the displacement values of unobserved vertices by solving the Laplace equation Δf = 0; it requires no training, is computationally efficient, and produces smooth results, but it yields overly smooth results and cannot express high-frequency motion details.70% similarUnverifiedAs generative models iterate, these logical flaws are rapidly diminishing, but as long as the underlying mechanism remains based on statistical learning rather than physical understanding, some form of logical loophole will be very difficult to eliminate entirely70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1131757API
curl https://kongchang.com/api/v1/knowledge/claims/1131757MCP
get_claim(id=1131757)