Good Papers

Showing papers from Institute of Computing, Chinese Academy of Sciences Show all papers

57%Worth a look
?Worth a lookVote to see the score

Flux: Online, Fine-Grained Data Scheduling for Training Machine Learning Interatomic Potentials

Yuanchang Zhou, Chen Wang, Hongtao Xu, Mingzhen Li and 2 more

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

– ReadersNo votes yet
1/20 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: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
88%Must read
?Must readVote to see the score

Compact SO(3) Equivariant Atomistic Foundation Models via Structural Pruning

Structural pruning of SO(3) equivariant atomistic models reduces inference cost while outperforming small from-scratch models on accuracy and compute.

Chen Wang, Siyu Hu, Guangming Tan, Weile Jia

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
15/20 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: 15 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 2/5