Publications

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Preprints & submissions

1. Submitted to AAAI 2027

   SIGMA: Semantic Identifier Grouping for Molecular Autoregression

   X. Wang, F. Dou, J. Bi, M. Song

2. Submitted to NeurIPS 2026

   Beyond Linear Depth Scaling: Diagnosing Piecewise Layer Reliability for Data-Free Model Merging (DIAL)

   X. Wang, K. Deng, F. Dou, J. Bi, J. Lu

3. arXiv preprint

   Leveraging Partial SMILES Validation Scheme for Enhanced Drug Design in Reinforcement Learning Frameworks

   X. Wang, J. Bi, M. Song

Peer-reviewed publications

1. Advances in Neural Information Processing Systems (NeurIPS), 2023

   Polyhedron Attention Module: Learning Adaptive-Order Interactions

   T. Zhu, F. Dou, X. Wang, J. Lu, J. Bi

2. Molecular Informatics 42(5), 2200215, 2023

   Fragment-based Deep Molecular Generation Using Hierarchical Chemical Graph Representation and Multi-resolution Graph Variational Autoencoder

   Z. Gao, X. Wang, B. Blumenfeld Gaines, X. Shi, J. Bi, M. Song

3. IEEE/ACM CHASE 2025

   Cross-platform Prediction of Depression Treatment Outcome Using Location Sensory Data on Smartphones

   S. Sahoo, C. Shende, M. Z. Hossain, P. Patel, Y. Niu, X. Wang, S. Ware, J. Bi

4. IEEE/ACM CHASE 2024

   Using Mobile Daily Mood and Anxiety Self-ratings to Predict Depression Symptom Improvement

   S. Sahoo, C. Shende, M. Z. Hossain, P. Patel, X. Wang, M. I. Mahmud, J. Bi

5. PACM IMWUT, 2023

   Predicting Symptom Improvement During Depression Treatment Using Sleep Sensory Data

   C. Shende, S. Sahoo, S. Sam, P. Patel, R. Morillo, X. Wang, S. Ware, J. Bi

6. BMC Systems Biology 12, 15-27, 2018

   Inferring Phenotypes from Substance Use via Collaborative Matrix Completion

   J. Lu, J. Sun, X. Wang, H. R. Kranzler, J. Gelernter, J. Bi

7. IEEE BIBM 2017

   Collaborative Phenotype Inference from Comorbid Substance Use Disorders and Genotypes

   J. Lu, J. Sun, X. Wang, H. R. Kranzler, J. Gelernter, J. Bi