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cs.CL2024★ 1 cited
Fundamental Problems With Model Editing: How Should Rational Belief Revision Work in LLMs?
Peter Hase, Thomas Hofweber, Xiang Zhou +2
The model editing problem concerns how language models should learn new facts about the world over time. While empirical research on model editing has drawn widespread attention, t…
cs.CL2024
Inducing Systematicity in Transformers by Attending to Structurally Quantized Embeddings
Yichen Jiang, Xiang Zhou, Mohit Bansal
Transformers generalize to novel compositions of structures and entities after being trained on a complex dataset, but easily overfit on datasets of insufficient complexity. We obs…