5 citations · 15 across the 24 of their papers we have counts for
5 papers · 1 filter
ExpertMuon-Compass: Alignment-Guided Step Sizes for Mixture-of-Experts Training
Omatharv Bharat Vaidya, Ashwin Vinod, Pedram Akbarian +3
Mixture-of-experts (MoE) language models send each token to a few experts, so each expert is trained on a different part of the data, and this part changes during training. With a…
When Many Answers Are Valid, Voting Fails: Symbolic Verification for Best-of-K Causal Reasoning in LLMs
Omatharv Bharat Vaidya, Connor Thomas Jerzak, Zayne Rea Sprague +2
Self-consistency assumes the most frequent answer among sampled reasoning traces is the most reliable, but this can fail in causal reasoning: samples often repeat the same confound…
Temporal Dynamics of Development Aid in Africa: Evidence from a Staggered Difference-in-Differences Study of China and World Bank Projects
Mattias Antar, Adel Daoud, Connor T. Jerzak
Subnational studies of aid effectiveness often rely on repeated cross-sections or nighttime lights, making it difficult to separate local treatment effects from baseline difference…
Queryable LoRA: Instruction-Regularized Routing Over Shared Low-Rank Update Atoms
Omatharv Bharat Vaidya, Connor T. Jerzak, Nhat Ho +1
We present a data-adaptive method for parameter-efficient fine-tuning of large neural networks. Standard low-rank adaptation methods improve efficiency by restricting each layer up…
Multiplication in Multimodal LLMs: Computation with Text, Image, and Audio Inputs
Samuel G. Balter, Ethan Jerzak, Connor T. Jerzak
Multimodal LLMs can accurately perceive numerical content across modalities yet fail to perform exact multi-digit multiplication when the identical underlying arithmetic problem is…