Author

E. M. Pari

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#machine learning Preprint Sep 2026

Test-Time Unlearning via Sparse Autoencoder

Machine unlearning aims to remove specific knowledge from a trained large language model (LLM) without retraining from scratch. Existing methods modify model weights via gradient ascent and its advances. While effective on certain benchmarks, these weight-based approaches exhibit a sharp forget-utility trade-off, where...

Pingzhi Li, Jinhao Duan, Vaishnav Tadiparthi et al. · 0 citations

Preprint Aug 2026

Bayesian Partner Modelling enables Adaptive Replanning for LLM Coordination

BayesBeliefAgent is introduced, which pairs a hierarchical LLM planner with a Bayesian tracking module and evaluates performance using replanning efficiency and the belief-action gap: the fraction of total decisions where an agent with a correct partner estimate executes a non-complementary skill.

Harsh Goel, A. S. Ellendula, Vaishnav Tadiparthi et al. · 1 citation