- University of California, Santa BarbaraUS314 papers
- Microsoft Research (United Kingdom)GB248 papers
- Massachusetts Institute of TechnologyUS170 papers
- University of California, BerkeleyUS170 papers
- University of WashingtonUS165 papers
- Stanford UniversityUS156 papers
- Carnegie Mellon UniversityUS149 papers
- ETH ZurichCH131 papers
- Princeton UniversityUS119 papers
- University of Maryland, College ParkUS108 papers
- California Institute of TechnologyUS107 papers
- Cornell UniversityUS98 papers
3,302 papers
Domain-Adaptive Pretraining Enhances Water Treatment Semantic Representation for Large-Scale Structured Literature Mining
Mudi Zhai, Ruihong Qiu, Qingyun Zeng +3
Water treatment research is expanding rapidly, but much of the knowledge acquired from this research remains scattered across unstructured literature. The field still lacks a dedic…
On Predicting Vulnerability Severity Using In-Context Learning: An Industrial Case Study
Daniel Rodriguez-Cardenas, David Nader Palacio, Anna Schmedding +8
Modern software systems require earlier and more scalable vulnerability severity assessment to reduce exposure to high-impact security flaws. Security analysts typically assign CVS…
Analytical solutions of 1D Maxwell's equations via infinite-order expansions
David Wei Ge
Analytical solutions to Maxwell's equations are essential for understanding the causal and instantaneous behavior of electromagnetic fields, yet they are challenging to obtain in o…
ECLAIR: A Causally-Grounded AI Framework for Scientific Discovery in Empirical Software Engineering
Alejandro Velasco, Daniel Rodriguez-Cardenas, Dipin Khati +2
The scientific method has long guided empirical research in Software Engineering (SE), but the complexity of modern software systems often hinders its systematic application. This…
Extreme Meta-Classification for Large-Scale Zero-Shot Retrieval
Sachin Yadav, Deepak Saini, Anirudh Buvanesh +6
We develop accurate and efficient solutions for large-scale retrieval tasks where novel (zero-shot) items can arrive continuously at a rapid pace. Conventional Siamese-style approa…
Generating Graph-Like Logical Rules for Knowledge Graph Reasoning via Diffusion Models
Haoxiang Cheng, Yunfei Wang, Chao Chen +5
Logical rules constitute a cornerstone of knowledge graph (KG) reasoning, valued for their interpretability and ability to model relational patterns. However, existing rule mining…