Open Source Infrastructure for Differentiable Density Functional Theory. - Advika Vidhyadhiraja; Arun Pa Thiagarajan; Shang Zhu; Venkat Viswanathan; Bharath Ramsundar (CoRR, 2023)

Differentiable Chemical Physics by Geometric Deep Learning for Gradient-based Property Optimization of Mixtures. - Shang Zhu; Bharath Ramsundar; Emil Annevelink; Hongyi Lin; Adarsh Dave; Pin-Wen Guan; Kevin Gering; Venkatasubramanian Viswanathan (CoRR, 2023)

Theme Work on Teamwork: Mapping Student Teaming Experiences in Design Projects. - Sara Beckman; Krina Patel; Qiuquan Gu; Shang Zhu; Alexander Cui; Jacob Yim (FIE, 2024)

Open-Source Fermionic Neural Networks with Ionic Charge Initialization. - Shai Pranesh; Shang Zhu; Venkat Viswanathan; Bharath Ramsundar (CoRR, 2024)

Scaling Instruction-tuned LLMs to Million-token Contexts via Hierarchical Synthetic Data Generation. - Linda He; Jue Wang; Maurice Weber; Shang Zhu; Ben Athiwaratkun; Ce Zhang (ICLR, 2025)

Scaling Instruction-Tuned LLMs to Million-Token Contexts via Hierarchical Synthetic Data Generation. - Linda He; Jue Wang; Maurice Weber; Shang Zhu; Ben Athiwaratkun; Ce Zhang 001 (CoRR, 2025)

Think Deep, Think Fast: Investigating Efficiency of Verifier-free Inference-time-scaling Methods. - Junlin Wang; Shang Zhu; Jon Saad-Falcon; Ben Athiwaratkun; Qingyang Wu; Jue Wang; Shuaiwen Leon Song; Ce Zhang 001; Bhuwan Dhingra; James Zou 001 (CoRR, 2025)

34 Examples of LLM Applications in Materials Science and Chemistry: Towards Automation, Assistants, Agents, and Accelerated Scientific Discovery. - Yoel Zimmermann; Adib Bazgir; Alexander Al-Feghali; Mehrad Ansari; Joshua D. Bocarsly; L. Catherine Brinson; Yuan Chiang; Defne Circi; Min-Hsueh Chiu; Nathan Daelman; Matthew L. Evans; Abhijeet Sadashiv Gangan; et al. (CoRR, 2025)

Improving Model Alignment Through Collective Intelligence of Open-Source LLMS. - Junlin Wang; Roy Xie; Shang Zhu; Jue Wang; Ben Athiwaratkun; Bhuwan Dhingra; Shuaiwen Leon Song; Ce Zhang 001; James Zou 001 (CoRR, 2025)

When Does Divide and Conquer Work for Long Context LLM? A Noise Decomposition Framework. - Zhen Xu 007; Shang Zhu; Jue Wang; Junlin Wang; Ben Athiwaratkun; Chi Wang; James Zou 001; Ce Zhang 001 (CoRR, 2025)

CLOUD: A Scalable and Physics-Informed Foundation Model for Crystal Representation Learning. - Changwen Xu; Shang Zhu; Venkatasubramanian Viswanathan (CoRR, 2025)

Shrinking the Generation-Verification Gap with Weak Verifiers. - Jon Saad-Falcon; Estefany Kelly Buchanan; Mayee F. Chen; Tzu-Heng Huang; Brendan McLaughlin; Tanvir Bhathal; Shang Zhu; Ben Athiwaratkun; Frederic Sala; Scott W. Linderman; Azalia Mirhoseini; Christopher Ré (CoRR, 2025)

DREAMS: Density Functional Theory Based Research Engine for Agentic Materials Simulation. - Ziqi Wang; Hongshuo Huang; Hancheng Zhao; Changwen Xu; Shang Zhu; Jan Janssen; Venkatasubramanian Viswanathan (CoRR, 2025)