From the 1 of 6 linked papers with an AI index.
6 papers
ORCA-bench: How Ready Are Language Model Agents for Oncall?
Albert Gong, Kyuseong Choi, Abhineet Agarwal +5
The paper presents ORCA-bench, a benchmark that evaluates large language model agents on on-call root cause analysis tasks using real telemetry data from a live microservice system…
One Pipeline, Many Transformers: Pattern-Specific Imputation Specialists for Tabular Missing Data
Jacob Feitelberg, Dwaipayan Saha, Kyuseong Choi +3
Missing data in tabular datasets forces practitioners into a hard choice: deploy a general-purpose imputer that may perform poorly for the problem at hand, or wait for someone to d…
N: A Unified Python Package and Test Bench for Nearest Neighbor-Based Matrix Completion
Caleb Chin, Aashish Khubchandani, Harshvardhan Maskara +7
Nearest neighbor (NN) methods have re-emerged as competitive tools for matrix completion, offering strong empirical performance and recent theoretical guarantees, including entry-w…
GOPO: Policy Optimization using Ranked Rewards
Kyuseong Choi, Dwaipayan Saha, Woojeong Kim +2
Standard reinforcement learning from human feedback (RLHF) trains a reward model on pairwise preference data and then uses it for policy optimization. However, while reward models…
Learning Counterfactual Distributions via Kernel Nearest Neighbors
Kyuseong Choi, Jacob Feitelberg, Caleb Chin +2
Consider a setting with multiple units (e.g., individuals, cohorts, geographic locations) and outcomes (e.g., treatments, times, items), where the goal is to learn a multivariate d…
Distributional Matrix Completion via Nearest Neighbors in the Wasserstein Space
Jacob Feitelberg, Kyuseong Choi, Anish Agarwal +1
We study the problem of distributional matrix completion: Given a sparsely observed matrix of empirical distributions, we seek to impute the true distributions associated with both…