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2020 – today
- 2025
[j1]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, Janine George, Hassan Harb, Ghazal Khalighinejad, Sartaaj Khan, Sascha Klawohn, Magdalena Lederbauer, Soroush Mahjoubi, Bernadette Mohr, Seyed Mohamad Moosavi, Aakash Naik, Aleyna Beste Ozhan, Dieter Plessers, Aritra Roy, Fabian Schöppach, Philippe Schwaller, Carla Terboven, Katharina Ueltzen, Yue Wu, Shang Zhu, Jan Janssen, Calvin Li, Ian T. Foster, Ben Blaiszik:
32 examples of LLM applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery. Mach. Learn. Sci. Technol. 6(2): 30701 (2025)- [c3]Linda He, Jue Wang, Maurice Weber, Shang Zhu, Ben Athiwaratkun, Ce Zhang:
Scaling Instruction-tuned LLMs to Million-token Contexts via Hierarchical Synthetic Data Generation. ICLR 2025 - [c2]Junlin Wang, Roy Xie, Shang Zhu, Jue Wang, Ben Athiwaratkun, Bhuwan Dhingra, Shuaiwen Leon Song, Ce Zhang, James Zou:
Improving Model Alignment Through Collective Intelligence of Open-Source Models. ICML 2025 - [i12]Linda He, Jue Wang, Maurice Weber, Shang Zhu, Ben Athiwaratkun, Ce Zhang:
Scaling Instruction-Tuned LLMs to Million-Token Contexts via Hierarchical Synthetic Data Generation. CoRR abs/2504.12637 (2025) - [i11]Junlin Wang, Shang Zhu, Jon Saad-Falcon, Ben Athiwaratkun, Qingyang Wu, Jue Wang, Shuaiwen Leon Song, Ce Zhang, Bhuwan Dhingra, James Zou:
Think Deep, Think Fast: Investigating Efficiency of Verifier-free Inference-time-scaling Methods. CoRR abs/2504.14047 (2025) - [i10]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, Janine George, Hassan Harb, Ghazal Khalighinejad, Sartaaj Khan, Sascha Klawohn, Magdalena Lederbauer, Soroush Mahjoubi, Bernadette Mohr, Seyed Mohamad Moosavi, Aakash Naik, Aleyna Beste Ozhan, Dieter Plessers, Aritra Roy, Fabian Schöppach, Philippe Schwaller, Carla Terboven, Katharina Ueltzen, Yue Wu, Shang Zhu, Jan Janssen, Calvin Li, Ian T. Foster, Ben Blaiszik:
34 Examples of LLM Applications in Materials Science and Chemistry: Towards Automation, Assistants, Agents, and Accelerated Scientific Discovery. CoRR abs/2505.03049 (2025) - [i9]Junlin Wang, Roy Xie, Shang Zhu, Jue Wang, Ben Athiwaratkun, Bhuwan Dhingra, Shuaiwen Leon Song, Ce Zhang, James Zou:
Improving Model Alignment Through Collective Intelligence of Open-Source LLMS. CoRR abs/2505.03059 (2025) - [i8]Zhen Xu, Shang Zhu, Jue Wang, Junlin Wang, Ben Athiwaratkun, Chi Wang, James Zou, Ce Zhang:
When Does Divide and Conquer Work for Long Context LLM? A Noise Decomposition Framework. CoRR abs/2506.16411 (2025) - [i7]Changwen Xu, Shang Zhu, Venkatasubramanian Viswanathan:
CLOUD: A Scalable and Physics-Informed Foundation Model for Crystal Representation Learning. CoRR abs/2506.17345 (2025) - [i6]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:
Shrinking the Generation-Verification Gap with Weak Verifiers. CoRR abs/2506.18203 (2025) - [i5]Ziqi Wang, Hongshuo Huang, Hancheng Zhao, Changwen Xu, Shang Zhu, Jan Janssen, Venkatasubramanian Viswanathan:
DREAMS: Density Functional Theory Based Research Engine for Agentic Materials Simulation. CoRR abs/2507.14267 (2025) - [i4]Yongchan Kwon, Shang Zhu, Federico Bianchi, Kaitlyn Zhou, James Zou:
ReasonIF: Large Reasoning Models Fail to Follow Instructions During Reasoning. CoRR abs/2510.15211 (2025) - 2024
- [c1]Sara Beckman
, Krina Patel, Qiuquan Gu, Shang Zhu, Alexander Cui, Jacob Yim:
Theme Work on Teamwork: Mapping Student Teaming Experiences in Design Projects. FIE 2024: 1-7 - [i3]Shai Pranesh, Shang Zhu, Venkat Viswanathan, Bharath Ramsundar:
Open-Source Fermionic Neural Networks with Ionic Charge Initialization. CoRR abs/2401.10287 (2024) - 2023
- [i2]Advika Vidhyadhiraja, Arun Pa Thiagarajan, Shang Zhu, Venkat Viswanathan, Bharath Ramsundar:
Open Source Infrastructure for Differentiable Density Functional Theory. CoRR abs/2309.15985 (2023) - [i1]Shang Zhu, Bharath Ramsundar, Emil Annevelink, Hongyi Lin, Adarsh Dave, Pin-Wen Guan, Kevin Gering, Venkatasubramanian Viswanathan:
Differentiable Chemical Physics by Geometric Deep Learning for Gradient-based Property Optimization of Mixtures. CoRR abs/2310.03047 (2023)
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