papers

Publications (6)

cs.LG2020

A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data

Matthew B. A. McDermott, Bret Nestor, Evan Kim +4

Multi-task learning (MTL) is a machine learning technique aiming to improve model performance by leveraging information across many tasks. It has been used extensively on various d…

cond-mat.supr-con2022

ScGAN: A Generative Adversarial Network to Predict Hypothetical Superconductors

Evan Kim, S. V. Dordevic

Despite having been discovered more than three decades ago, High Temperature Superconductors (HTSs) lack both an explanation for their mechanisms and a systematic way to search for…

q-fin.CP2022

Replicating Portfolios: Constructing Permissionless Derivatives

Estelle Sterrett, Waylon Jepsen, Evan Kim

The current design space of derivatives in Decentralized Finance (DeFi) relies heavily on oracle systems. Replicating market makers (RMMs) provide a mechanism for converting specif…

cs.CV2026

Scaling View Synthesis Transformers

Evan Kim, Hyunwoo Ryu, Thomas W. Mitchel +1

Geometry-free view synthesis transformers have recently achieved state-of-the-art performance in Novel View Synthesis (NVS), outperforming traditional approaches that rely on expli…

cs.LG2026

Humanity's Last Exam

Long Phan, Alice Gatti, Ziwen Han +1144

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…

cs.RO2026

Turning Video Models into Generalist Robot Policies

Sizhe Lester Li, Evan Kim, Xingjian Bai +4

Video generative models have emerged as a promising robotics backbone, capable of generating videos that depict the completion of complex tasks across embodiments and environments.…