method
active
method:equal-weighting-ewEqual Weighting (EW)
Baseline that minimizes sum of task losses with equal weights.
Neighborhood — ranked by edge-count
Artifacts (1)
artifact
- The paper proposing the Dual-Balancing Multi-Task Learning method.
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Baseline MTL approach minimizing sum of task losses with equal weights; suffers from task balancing
- Loss balancing using homoscedastic uncertainty.
- Emotional intelligence benchmark (171 problems) used to check if activation capping degrades soft skills
- Discord mentioned where Gwern spoke.
- The space of the model's parameter matrices, where VPD operations take place.
- EI and normalized EI could serve as a unified metric for out-of-distribution generalization.claim0.700Conjecture that maximizing EI yields causal representations invariant to distribution shifts.
- Editing network weights to test predictions about circuit function; proposed as falsifiability test for circuit claims
- Quantitative study varying representational familiarity via numeral bases B10/B8/B9 at fixed computational complexity