Benchmarks
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
Benchmarks has 22 facts recorded in Dontopedia across 15 references.
Mostly:used for evaluating(1), suspected as training data(1), for(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (18)
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.
areComingInAre Coming in(1)
- Anchor Kan Results
ex:anchor-kan-results
assertsSuperiorityConfidentlyAsserts Superiority Confidently(1)
- Lisamegawatts
ex:lisamegawatts
assertsTrainingOnAsserts Training on(1)
- Proposition Most Models Trained on Benchmarks
ex:proposition-most-models-trained-on-benchmarks
causesBadMeasurementsCauses Bad Measurements(1)
- Gpu Hogging
ex:gpu-hogging
causesSlownessCauses Slowness(1)
- Other Peoples Code
ex:other-peoples-code
comparedAgainstCompared Against(1)
- Historical Data
ex:historical-data
comparedWithCompared With(1)
- Historical Data
ex:historical-data
comparesCompares(1)
- Compare With Data
ex:compare-with-data
depictsVerificationDepicts Verification(1)
- Screenshot 2026 04 04 at 1 24 28 Pm Png
ex:screenshot-2026-04-04-at-1-24-28-pm-png
focusesOnTopicFocuses on Topic(1)
- Chat Conversation
ex:chat-conversation
hasLotsOfHas Lots of(1)
- Lisamegawatts
ex:lisamegawatts
identifiesSlowPartIdentifies Slow Part(1)
- Lisamegawatts
ex:lisamegawatts
isNaturalNextStepIs Natural Next Step(1)
- Beating Sparsemax Entmax
ex:beating-sparsemax-entmax
knowsFromExperienceKnows From Experience(1)
- Lisamegawatts
ex:lisamegawatts
performedInPerformed in(1)
- Fed Sym
ex:fed-sym
potentiallyOverfitToPotentially Overfit to(1)
- AI Models
ex:ai-models
questionedForRealUtilityQuestioned for Real Utility(1)
- AI Models
ex:ai-models
usesTablesForEvidenceUses Tables for Evidence(1)
- Xenonfun
ex:xenonfun
Other facts (22)
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.
| Predicate | Value | Ref |
|---|---|---|
| Used for Evaluating | AI Models | [1] |
| Suspected As Training Data | AI Models | [1] |
| For | Harmonic Approach | [2] |
| Measure Matrix Multiply Time | 1024^3, 2048^3 | [3] |
| Performed on Mps | null | [4] |
| Include L1024 | B256b3d | [5] |
| Are Necessary for | Evaluation | [6] |
| Slow Due to | Other Peoples Code | [7] |
| Measure Convergence Speed | null | [8] |
| Measure Parameter Counts | true | [9] |
| Match Existing Precision Behavior | Gated Cumsum Real Existing | [9] |
| Assume Float32 Standard | true | [9] |
| Measure Time in Milliseconds | true | [9] |
| Use Float32 Precision Throughout | true | [9] |
| References Lohe Sync Prototype | Metal Kernel | [10] |
| Are Reproducible | null | [11] |
| Were Conducted | true | [12] |
| Intended for Training on | null | [13] |
| Essential for Validation | null | [14] |
| Presupposed to Exist | null | [14] |
| Compared With | Historical Data | [15] |
| Compared Against | Historical Data | [15] |
Timeline
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References (15)
ctx:discord/blah/models/part-6ctx:discord/blah/omega/part-1212ctx:discord/blah/training-and-evals/part-31ctx:discord/blah/watt-activation/part-8ctx:discord/blah/watt-activation/part-68ctx:discord/blah/watt-activation/part-161ctx:discord/blah/watt-activation/part-308ctx:discord/blah/watt-activation/part-317ctx:discord/blah/watt-activation/part-380ctx:discord/blah/watt-activation/part-454ctx:discord/blah/watt-activation/part-449ctx:discord/blah/watt-activation/part-461ctx:discord/blah/models/part-5ctx:discord/blah/omega/part-1213ctx:claims/beam/d08830f6-b282-4af7-b81f-6ba8f14334a9- full textbeam-chunktext/plain1 KB
doc:beam/d08830f6-b282-4af7-b81f-6ba8f14334a9Show excerpt
1. **Research Benchmarks**: Look for industry reports or guidelines that provide time estimates for common documentation tasks. 2. **Compare with Your Data**: Compare these benchmarks with your historical data to see if they align or if adj…
See also
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