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ICML

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RESEARCH · 1 SOURCE · Apple Machine Learning Research

Tri-modal Masked Diffusion Models pretrained from scratch with SDE reparameterization and 3B demo

This paper introduces the first tri-modal Masked Diffusion Models (MDM) pretrained from scratch on text, image–text, and audio–text data, presents a large-scale systematic study of scaling laws, modality mixing, noise schedules and batch-size effects, and proposes an SDE-based reparameterization that decouples physical and logical batch sizes. The authors also release a preliminary unified model at ~3B parameters (trained on ~6.4T tokens) showing competitive results in text generation, text-to-image and text-to-speech tasks.

7.0

RESEARCH · 1 SOURCE · arXiv cs.AI

ScientistTwo (arXiv:2609.19644v1): autonomous multi-agent framework for end-to-end scientific discovery

A new arXiv preprint (arXiv:2609.19644v1) introduces ScientistTwo, a fully autonomous multi‑agent framework that—given an initial research problem—claims to establish baselines, formulate hypotheses, run experiments and ablations, and validate results via a closed‑loop simulated peer‑review engine without human intervention. The paper reports benchmarking against work from top ML venues (ICLR, ICML, NeurIPS) and asserts that ScientistTwo autonomously produces expert‑level, publishable papers and executable code that outperform human state‑of‑the‑art models and receive higher average ratings from automated reviewers (claims as stated by the authors in the preprint).

8.0