Alexander Theus

@TheusResearch

PhD candidate in Machine Learning @ETH_en and @MPI_IS.

scholar.google.com/citations?user… Joined May 2024

57 Following 108 Followers 28 Posts

Latest posts 4

Self-supervised transcriptomic FMs are pretrained on millions of gene-expression profiles, yet often fail to beat simple supervised baselines on clinical tasks.

Why?

Our new work suggests the pretraining objective may matter more than scale.

📄arxiv.org/abs/2610.08694

1/8

Alexander Theus @TheusResearch Jun 22

👇 Check out our new preprint: FPRM (Fixed-Point Reasoning Model).
• No ACT head: loop to a fixed point, with convergence as the halt signal.
• No hierarchy: a single loop beats HRM/TRM variants!
• SOTA among 7M models: Sudoku-Extreme 94.2%, Maze-Hard 87.0%, ARC-AGI-1 47.5%.

Sajad Movahedi @Sajad_Movahedi_ Jun 22

Looped models scale compute by iterating in depth, demonstrating great potential in reasoning. But when should the looping stop, and how to keep it trainable at tens of thousands of unrolled layers? FPRM solves both. (1/7)

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Alexander Theus @TheusResearch Sep 19, 2025

Excited to announce that our paper has been accepted as an Oral at NeurIPS 2025! 🥳

Alexander Theus @TheusResearch Jul 9, 2025

1/ 🚨 New paper alert! 🚨
We explore a key question in deep learning:
Can independently trained Transformers be linearly connected in weight space — without a loss barrier?
Yes — if you uncover their rich symmetries.
📄 arXiv: arxiv.org/abs/2506.22712

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Alexander Theus @TheusResearch Jul 9, 2025

1/ 🚨 New paper alert! 🚨
We explore a key question in deep learning:
Can independently trained Transformers be linearly connected in weight space — without a loss barrier?
Yes — if you uncover their rich symmetries.
📄 arXiv: arxiv.org/abs/2506.22712