Interesting work by @aardauzunoglu and @ZAlvin39105 that frames weak-to-strong generalization as a data selection problem, i..e "which weak labels should the student trust?" (to appear in ICML)
Arda Uzunoğlu@aardauzunoglu
As LLMs surpass humans on many fronts, how can we keep training stronger models?
Our ICML 2026 paper studies this via weak-to-strong generalization and shows that learning when to trust the weak teacher may be key.
Trust Functions: Near-Lossless Weak-to-Strong Generalization 🧵
5:25 AM · Jun 10, 2026 · 769 Views
