Mehak Preet Dhaliwal — accepted AI-conference papers

2025

NutriBench: A Dataset for Evaluating Large Language Models in Nutrition Estimation from Meal Descriptions

Mehak Preet Dhaliwal, Andong Hua, Laya Pullela, Ryan Burke, Yao Qin

ICLR 2025poster

Accurate nutrition estimation helps people make informed dietary choices and is essential in the prevention of serious health complications. We present NutriBench, the first publicly available natural language meal description nutrition benchmark. NutriBench consists of 11,857 meal descriptions gene…

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2022

Infinite Recommendation Networks: A Data-Centric Approach

Noveen Sachdeva, Mehak Preet Dhaliwal, Carole-Jean Wu, Julian McAuley

NeurIPS 2022accept

We leverage the Neural Tangent Kernel and its equivalence to training infinitely-wide neural networks to devise $\infty$-AE: an autoencoder with infinitely-wide bottleneck layers. The outcome is a highly expressive yet simplistic recommendation model with a single hyper-parameter and a closed-form s…

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