Dontopedia

LoheOptimizer

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-06.)

LoheOptimizer has 36 facts recorded in Dontopedia across 6 references, with 3 live disagreements.

36 facts·31 predicates·6 sources·3 in dispute

Mostly:evaluated negatively(2), step includes(2), uses(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (6)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

mentionsEntityMentions Entity(2)

isInformativeForIs Informative for(1)

refersToEntityRefers to Entity(1)

statedKnowledgeAboutStated Knowledge About(1)

superiorToLoheSuperior to Lohe(1)

Other facts (33)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

33 facts
PredicateValueRef
Evaluated NegativelyGpt 2 Scale[1]
Evaluated Negativelynull[2]
Step IncludesActivation Forward Pass[4]
Step IncludesSynchronization Update[4]
UsesLohe Synchronization Equation[1]
Lacks Global Gradienttrue[1]
Empirically FailsGpt 2 Scale[1]
Fails at ScaleGpt 2 Scale[1]
Has Weak Signallayer-local sync signal is too weak to propagate coherent learning through 12 layers without a global gradient[1]
Updates Layer Locallyeach layer's weights[1]
Motivated byif Lohe sync on S^{d-1} is the right dynamics for the system, can it self-organize without needing a loss gradient?[1]
Commits to Geometric Ontologytangent-space Kuramoto step[1]
Is Gradient Freetrue[1]
Implements Oscillatorsnull[2]
Has IssuesBehavior Step Issues[2]
Has No Gradient Flow Through Couplingnull[2]
Has Three Compounding Problemsnull[2]
Is Flying Blind toOscillators Syncing[2]
Named After LoheLohe[3]
Confirms Not Learning Structure From Scratchtrue[3]
Exhibits Flatline Across Metricsall metrics[3]
Fails to Learn Structurefrom scratch[3]
Has Sys Beta Stuck at5.8[3]
Has Sys R Stuck at0.59[3]
Lacks Phase Orderingtrue[3]
Shows Trending Down1k Steps[3]
PropertyGradient Free[4]
Uses EquationLohe Synchronization Equation[4]
Lacks ComponentAutodiff[4]
Learning SignalGeometric Synchronization[4]
Has ComponentInternal Get Temperature Scheduler[5]
TracksKuramoto Order Parameter[5]
Observed Behavior Scopefinetune[6]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

36 undated
—
usesblah/watt-activation/part-122
ex:lohe-synchronization-equation
—
lacksGlobalGradientblah/watt-activation/part-122
true
—
empiricallyFailsblah/watt-activation/part-122
ex:gpt-2-scale
—
failsAtScaleblah/watt-activation/part-122
ex:gpt-2-scale
—
hasWeakSignalblah/watt-activation/part-122
layer-local sync signal is too weak to propagate coherent learning through 12 layers without a global gradient
—
updatesLayerLocallyblah/watt-activation/part-122
each layer's weights
—
motivatedByblah/watt-activation/part-122
if Lohe sync on S^{d-1} is the right dynamics for the system, can it self-organize without needing a loss gradient?
—
evaluatedNegativelyblah/watt-activation/part-122
ex:gpt-2-scale
—
commitsToGeometricOntologyblah/watt-activation/part-122
tangent-space Kuramoto step
—
isGradientFreeblah/watt-activation/part-122
true
—
implementsOscillatorsblah/watt-activation/part-188
null
—
hasIssuesblah/watt-activation/part-188
ex:behavior-step-issues
—
hasNoGradientFlowThroughCouplingblah/watt-activation/part-188
null
—
evaluatedNegativelyblah/watt-activation/part-188
null
—
hasThreeCompoundingProblemsblah/watt-activation/part-188
null
—
isFlyingBlindToblah/watt-activation/part-188
ex:oscillators-syncing
—
namedAfterLoheblah/watt-activation/part-186
ex:lohe
—
confirmsNotLearningStructureFromScratchblah/watt-activation/part-186
true
—
exhibitsFlatlineAcrossMetricsblah/watt-activation/part-186
all metrics
—
failsToLearnStructureblah/watt-activation/part-186
from scratch
—
hasSysBetaStuckAtblah/watt-activation/part-186
5.8
—
hasSysRStuckAtblah/watt-activation/part-186
0.59
—
lacksPhaseOrderingblah/watt-activation/part-186
true
—
showsTrendingDownblah/watt-activation/part-186
ex:1k-steps
—
labelblah/watt-activation/122
LoheOptimizer
—
propertyblah/watt-activation/122
ex:gradient-free
—
usesEquationblah/watt-activation/122
ex:lohe-synchronization-equation
—
stepIncludesblah/watt-activation/122
ex:activation-forward-pass
—
stepIncludesblah/watt-activation/122
ex:synchronization-update
—
lacksComponentblah/watt-activation/122
ex:autodiff
—
learningSignalblah/watt-activation/122
ex:geometric-synchronization
—
labelblah/watt-activation/179
LoheOptimizer
—
hasComponentblah/watt-activation/179
ex:internal-get-temperature-scheduler
—
tracksblah/watt-activation/179
ex:kuramoto-order-parameter
—
labelblah/watt-activation/213
loheoptimizer
—
observedBehaviorScopeblah/watt-activation/213
finetune

References (6)

6 references
  1. [1]Part 12210 facts
    ctx:discord/blah/watt-activation/part-122
  2. [2]Part 1886 facts
    ctx:discord/blah/watt-activation/part-188
  3. [3]Part 1868 facts
    ctx:discord/blah/watt-activation/part-186
  4. [4]1227 facts
    ctx:discord/blah/watt-activation/122
    • full textwatt-activation-122
      text/plain3 KBdoc:agent/watt-activation-122/57649dd0-cec5-4d9a-bc09-bec5f2db2137
      Show excerpt
      [2026-03-09 01:19] xenonfun: ⏺ BP = Backpropagation — whether the optimizer computes gradients via automatic differentiation or not. Adam / RotAdamW use standard backprop: 1. Forward pass → compute loss 2. nn.value_and_grad() → autod…
  5. [5]1793 facts
    ctx:discord/blah/watt-activation/179
    • full textwatt-activation-179
      text/plain3 KBdoc:agent/watt-activation-179/0c4c7b51-a557-4122-8ca0-a6c8c3958503
      Show excerpt
      [2026-03-10 01:19] lisamegawatts: https://github.com/google-research/language/tree/master/language/canine [2026-03-10 01:23] xenonfun: they have some interesting datasets: https://huggingface.co/datasets/google/MapTrace https://huggingface.…
  6. [6]2132 facts
    ctx:discord/blah/watt-activation/213
    • full textwatt-activation-213
      text/plain2 KBdoc:agent/watt-activation-213/16ef74b4-a6af-4b66-91eb-9cfddab2b495
      Show excerpt
      [2026-03-11 04:15] xenonfun: oh yeah I knew the loheoptimizer so far only seemed to work on finetune [2026-03-11 04:15] lisamegawatts: yes if it wasn't aware loss would not go down, the rotational adam is fine [2026-03-11 04:16] xenonfun: o…

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