Good Papers

Showing papers from Kakao Corp Show all papers

86%Must read
?Must readVote to see the score

Mixture-Trained Merging for Unified Multi-Objective Models

Mixture-Trained Merging trains multi-objective branches on biased data mixtures to enable compatible weight-space merging, outperforming naive merging while preserving distinct capabilities.

SeongHyeon Kim, Chaeyun Jang, Seungyoo Lee, Jiyeon Ham and 3 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
14/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 2/5