Rule Extrapolation in Language Modeling: A Study of Compositional Generalization on OOD Prompts

Anna Mészáros, Szilvia Ujváry, Wieland Brendel, Patrik Reizinger, Ferenc Huszár
2/3/2026

No confident code implementation found for this paper.

Semantic Scholar

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

(Mis)Fitting Scaling Laws: A Survey of Scaling Law Fitting Techniques in Deep Learning

92% match2026

Exploiting Structure in Offline Multi-Agent RL: The Benefits of Low Interaction Rank

91% match2026

Building on Efficient Foundations: Effective Training of LLMs with Structured Feedforward Layers

90% match1 repo202026

Symmetry-Driven Discovery of Dynamical Variables in Molecular Simulations

90% match2026

Robust Situational Reinforcement Learning in Face of Context Disturbances

89% match2026

Fantastic Robustness Measures: The Secrets of Robust Generalization

88% match1 repo472026

Cite this paper

@article{mszros2026rule,
  title  = {Rule Extrapolation in Language Modeling: A Study of Compositional Generalization on OOD Prompts},
  author = {Anna Mészáros and Szilvia Ujváry and Wieland Brendel and Patrik Reizinger and Ferenc Huszár},
  year   = {2026},
  url    = {https://www.semanticscholar.org/paper/41ea8c164fcc22efcd557b50ea8718872f610fc4},
  journal = {NEURIPS 2024 2024}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/41ea8c164fcc22efcd557b50ea8718872f610fc4.svg)](https://codeofpaper.com/paper/41ea8c164fcc22efcd557b50ea8718872f610fc4)

Discussion