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Willie Neiswanger

University of Southern California

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#artificial intelligence Preprint Sep 2026

BOReFT: Manifold Steering of Language Models for Black-box Optimization

BOReFT is introduced, which learns a compact, low-dimensional space of hidden-state interventions in a frozen language model, and uses this space as the search domain for Bayesian optimization with an external scoring function, and provides a principled new bridge between discrete proposal spaces of LLM-based search an...

Dhruv Agarwal, Rico Angell, Kavitha Srinivas et al. · 0 citations

Rethinking RL for LLM Reasoning: It's Sparse Policy Selection, Not Capability Learning

ReasonMaxxer, a minimal RL-free method that applies contrastive loss only at entropy-gated decision points, matches or exceeds full RL performance while requiring only tens of problems and minutes of single-GPU training, a reduction in training cost of roughly three orders of magnitude.

Ömer Faruk Akgül, Rajgopal Kannan, Willie Neiswanger et al. · 3 citations · ⚡1
Book Jul 2026

Trustworthy Protein-Ligand Binding Affinity Prediction via Reliability-Aware Multi-Engine Fusion

To the knowledge, RELIABLE-BA is the first multi-engine binding affinity prediction framework to combine evidential fusion with context-dependent reliability, offering a principled path toward trustworthy AI-guided drug discovery.

Yongchan Hong, Defu Cao, Wenjin Liu et al. · 0 citations

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