Tao Liang

Tao Liang has 2 papers in our library, in 2025, most of them on Language models & pretraining; often with Xiang Wang, An Zhang, Baolong Bi.

2 papers in our library · 2025

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Neuron-Level Sequential Editing for Large Language Models (2025 · 15 citations)
Large language models store facts that go out of date, and full retraining is expensive. Parameter-editing methods such as ROME and MEMIT work well for a single round of edits. When edits are applied one after another, however, they tend to lose earlier edits ("model forgetting") and can collapse into incoherent…
Route Sparse Autoencoder to Interpret Large Language Models (2025 · 11 citations)
Sparse autoencoders (SAEs) are a popular way to break LLM activations into interpretable, mostly monosemantic features.

8 co-authors with a page, the most papers together first.

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Papers of our library cite their works 21 times (of the 149,439 papers whose bibliographies we read); 10 citing papers with a page here →.

Updated 31 October 2026