Multi-Task Learning
Multi-task learning aims to learn multiple different tasks simultaneously while maximizing performance on one or all of the tasks.
( Image credit: Cross-stitch Networks for Multi-task Learning )
Papers
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Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | PCGrad | ∆m% | 125.7 | — | Unverified |
| 2 | CAGrad | ∆m% | 112.8 | — | Unverified |
| 3 | IMTL-G | ∆m% | 77.2 | — | Unverified |
| 4 | Nash-MTL | ∆m% | 62 | — | Unverified |
| 5 | BayesAgg-MTL | ∆m% | 53.7 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | SwinMTL | mIoU | 76.41 | — | Unverified |
| 2 | Nash-MTL | mIoU | 75.41 | — | Unverified |
| 3 | MultiObjectiveOptimization | mIoU | 66.63 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | Gumbel-Matrix Routing | Average Accuracy | 93.52 | — | Unverified |
| 2 | Mixture-of-Experts | Average Accuracy | 92.19 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | MGDA-UB | Error | 8.25 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | BayesAgg-MTL | delta_m | -2.23 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | LETR | FH | 83.3 | — | Unverified |