Logical Rule Induction and Theory Learning Using Neural Theorem Proving. - Andres Campero; Aldo Pareja; Tim Klinger; Josh Tenenbaum 001; Sebastian Riedel 001 (CoRR, 2018)

Scalable Graph Learning for Anti-Money Laundering: A First Look. - Mark Weber; Jie Chen 007; Toyotaro Suzumura; Aldo Pareja; Tengfei Ma 001; Hiroki Kanezashi; Tim Kaler; Charles E. Leiserson; Tao B. Schardl (CoRR, 2018)

EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs. - Aldo Pareja; Giacomo Domeniconi; Jie Chen 007; Tengfei Ma 001; Toyotaro Suzumura; Hiroki Kanezashi; Tim Kaler; Charles E. Leiserson (CoRR, 2019)

EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs. - Aldo Pareja; Giacomo Domeniconi; Jie Chen 007; Tengfei Ma 001; Toyotaro Suzumura; Hiroki Kanezashi; Tim Kaler; Tao B. Schardl; Charles E. Leiserson (AAAI, 2020)

PARAD: A Work-Efficient Parallel Algorithm for Reverse-Mode Automatic Differentiation. - Tim Kaler; Tao B. Schardl; Brian Xie; Charles E. Leiserson; Jie Chen 007; Aldo Pareja; Georgios Kollias (APOCS, 2021)

Curiosity-driven Red-teaming for Large Language Models. - Zhang-Wei Hong; Idan Shenfeld; Tsun-Hsuan Wang; Yung-Sung Chuang; Aldo Pareja; James R. Glass; Akash Srivastava; Pulkit Agrawal 001 (ICLR, 2024)

LAB: Large-Scale Alignment for ChatBots. - Shivchander Sudalairaj; Abhishek Bhandwaldar; Aldo Pareja; Kai Xu 016; David D. Cox; Akash Srivastava (CoRR, 2024)

Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs. - Aldo Pareja; Nikhil Shivakumar Nayak; Hao Wang; Krishnateja Killamsetty; Shivchander Sudalairaj; Wenlong Zhao 001; Seungwook Han; Abhishek Bhandwaldar; Guangxuan Xu; Kai Xu 016; Ligong Han; Luke Inglis; et al. (ICLR, 2025)

Sculpting Subspaces: Constrained Full Fine-Tuning in LLMs for Continual Learning. - Nikhil Shivakumar Nayak; Krishnateja Killamsetty; Ligong Han; Abhishek Bhandwaldar; Prateek Chanda; Kai Xu 016; Hao Wang; Aldo Pareja; Oleg Silkin; Mustafa Eyceoz; Akash Srivastava (CoRR, 2025)