1 citations · 1 across the 9 of their papers we have counts for
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Inner Momentum for Differentially Private Muon
Bishnu Bhusal, Minh Vu, Ben Southworth +3
Differentially private training clips each per-example gradient before adding noise. This clipping is radial for each example, yet unequal clipping factors can distort the relative…
One Model, Two Physical Stories: Auditing Misalignment in Multi-Modal World Modeling
Geigh Zollicoffer, Minh Vu, Rajiv Ranasinghe +1
World models, systems that generate what happens next given current environmental conditions, are increasingly being implemented with multi-modal generation in mind. However, gener…
Sanity Checks for Long-Form Hallucination Detection
Geigh Zollicoffer, Minh Vu, Hongli Zhan +2
Hallucination detection methods for large language models increasingly operate on chain-of-thought reasoning traces, yet it remains unclear whether they evaluate the reasoning itse…
Trustworthy Agentic AI Requires Deterministic Architectural Boundaries
Manish Bhattarai, Minh Vu
Current agentic AI architectures are fundamentally incompatible with the security and epistemological requirements of high-stakes scientific workflows. The problem is not inadequat…
Privacy Enhanced PEFT: Tensor Train Decomposition Improves Privacy Utility Tradeoffs under DP-SGD
Pradip Kunwar, Minh Vu, Maanak Gupta +1
Fine-tuning large language models on sensitive data poses significant privacy risks, as membership inference attacks can reveal whether individual records were used during training…