Publications (6)
DBLP: Phase-Aware Bounded-Loss Transport for Burst-Resilient Distributed ML Training
Zechen Ma, Zixi Qu, Jinyan Yi +2
Distributed machine learning (ML) training has become a necessity with the prevalence of billion to trillion-parameter-scale models. While prior work has improved training efficien…
Logic Bug Detection and Localization Using Symbolic Quick Error Detection
Eshan Singh, David Lin, Clark Barrett +1
We present Symbolic Quick Error Detection (Symbolic QED), a structured approach for logic bug detection and localization which can be used both during pre-silicon design verificati…
A Data-Driven Approach for Semantic Role Labeling from Induced Grammar Structures in Language
Vivek Datla, David Lin, Max Louwerse +1
Semantic roles play an important role in extracting knowledge from text. Current unsupervised approaches utilize features from grammar structures, to induce semantic roles. The dep…
Solving Cold-Start Problem in Large-scale Recommendation Engines: A Deep Learning Approach
Jianbo Yuan, Walid Shalaby, Mohammed Korayem +3
Collaborative Filtering (CF) is widely used in large-scale recommendation engines because of its efficiency, accuracy and scalability. However, in practice, the fact that recommend…
Feature-Weighted Linear Stacking
Joseph Sill, Gabor Takacs, Lester Mackey +1
Ensemble methods, such as stacking, are designed to boost predictive accuracy by blending the predictions of multiple machine learning models. Recent work has shown that the use of…
OpenAI GPT-5 System Card
Aaditya Singh, Adam Fry, Adam Perelman +483
This is the system card published alongside the OpenAI GPT-5 launch, August 2025. GPT-5 is a unified system with a smart and fast model that answers most questions, a deeper reason…