concept
active
concept:task-balancing

Task balancing

The problem of ensuring all tasks in MTL perform well, avoiding dominance by some tasks.

Neighborhood — ranked by edge-count

Related by similarity (8)

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

  • Core challenge where disparity in loss and gradient scales among tasks leads to performance compromises
  • Motivation for the proposed method.
  • Task Difficultyconcept0.799
    The paper identifies task difficulty as a key moderator: easy MMLU questions show performative CoT, hard GPQA-Diamond questions show genuine reasoning
  • Novel task asking which of two sentences received a stronger injection, using matched-pairs design to control for positional bias
  • Novel MTL method combining loss-scale and gradient-magnitude balancing
  • Hinting Taskmethod0.767
    One of four ToM tasks analyzed; requires inferring speaker intent from indirect hints; scored 0/1.
  • Addressing disparity in loss magnitudes across tasks at the loss level
  • Task weightconcept0.761
    Coefficient weighting each task loss in the MTL objective.