{"total":3,"items":[{"citing_arxiv_id":"2606.22377","ref_index":23,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Multigrid Training for Molecular Generation using Graph Neural Networks","primary_cat":"cs.LG","submitted_at":"2026-06-21T07:56:31+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"Multigrid training accelerates convergence and improves generalization for receptor-conditioned 3D ligand generation by transferring parameters from coarse to fine graph and voxel resolutions.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.28287","ref_index":10,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"AtomComposer: Discovering Chemical Space from First Principles with Reinforcement Learning","primary_cat":"cs.LG","submitted_at":"2026-05-27T10:35:28+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":8.0,"formal_verification":"none","one_line_summary":"AtomComposer uses online RL with multi-composition training to discover up to 10x more valid 3D isomers on unseen chemical formulas than single-composition baselines.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2510.03046","ref_index":54,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Bayesian E(3)-Equivariant Interatomic Potential with Iterative Restratification of Many-body Message Passing","primary_cat":"cs.LG","submitted_at":"2025-10-03T14:28:10+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"Bayesian E(3)-equivariant MLPs with joint energy-force NLL loss achieve competitive accuracy while enabling uncertainty-guided active learning, OOD detection, and calibration.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null}],"limit":50,"offset":0}