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From the 1 of 5 linked papers with an AI index.

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5 papers

cs.LG2026

Uncertainty Is Not Enough: Value-of-Information Routing for Mixtures of LoRA Experts

Tom Saliencro, Rohan Desai, Priya Nair +2

Mixtures of low-rank adaptation experts increase parameter-efficient capacity by routing each input through a subset of adapters. Recent dynamic routers activate more experts when…

cs.LG2026

Spend Experts Where You Are Unsure: Confidence-Adaptive Routing for Mixture-of-Experts LoRA

Tom Saliencro, Rohan Desai, Priya Nair +2

The paper introduces CARE, a confidence-adaptive routing method for Mixture-of-Experts LoRA that dynamically selects the number of experts per token based on the router’s uncertain…

cs.LG2026

FRAME: Learning the Adaptation Domain with a Mixture of Fractional-Fourier Experts

Tom Saliencro, Maya Lindqvist, Rohan Desai +2

Parameter-efficient fine-tuning (PEFT) reparameterizes weight updates in a fixed basis: low-rank adapters operate in the spatial domain, while a recent line of spectral methods ope…

cs.LG2026

PLaID++: A Preference Aligned Language Model for Targeted Inorganic Materials Design

Andy Xu, Rohan Desai, Larry Wang +2

Reinforcement Learning from Verifiable Rewards (RLVR) has emerged as a promising approach to improve correctness in LLMs, however, in many scientific problems, the objective is not…

cs.CV2026

DualResolution Residual Architecture with Artifact Suppression for Melanocytic Lesion Segmentation

Vikram Singh, Kabir Malhotra, Rohan Desai +3

Lesion segmentation, in contrast to natural scene segmentation, requires handling subtle variations in texture and color, frequent imaging artifacts (such as hairs, rulers, and bub…