3 citations · 7 across the 7 of their papers we have counts for
8 papers
Distillation, Self-Training, and the Fragility of Learned Chemical Reasoning
Anagha Aneesh, Sebastian Ibarraran, Frank Hu +2
Automating synthesis planning for small-molecule drug design requires chemical reasoners that are accurate as well as open to inspection and adaptation, yet frontier language model…
Training Large Language Models for Small-Molecule Design with Synthetic Task Scaling
Frank Hu, Shriram Chennakesavalu, Zichen Wang +5
Designing viable drug candidates requires searching a combinatorially large and rugged chemical space for molecules that satisfy multiple, often competing, objectives. Large langua…
Frontier LLMs are effective batch optimizers: Assessing reasoning models in continuous and discrete settings
Frank Hu, Shriram Chennakesavalu, David Graff
Frontier large language models (LLMs) have become attractive priors for optimization due to their large-scale pretraining that enables them to navigate a variety of optimization se…
Pushing the limits of one-dimensional NMR spectroscopy for automated structure elucidation using artificial intelligence
Frank Hu, Jonathan M. Tubb, Dimitris Argyropoulos +5
One-dimensional NMR spectroscopy is one of the most widely used techniques for the characterization of organic compounds and natural products. For molecules with up to 36 non-hydro…
Reducible Iterated Graph Systems: multiscale-freeness and multifractals
Nero Ziyu Li, Frank Xin Hu, Thomas Britz
Iterated Graph Systems (IGS) transplant ideas from fractal geometry into graph theory. Building on this framework, we extend Edge IGS from the primitive to the reducible setting. W…
Accurate and efficient structure elucidation from routine one-dimensional NMR spectra using multitask machine learning
Frank Hu, Michael S. Chen, Grant M. Rotskoff +2
Rapid determination of molecular structures can greatly accelerate workflows across many chemical disciplines. However, elucidating structure using only one-dimensional (1D) NMR sp…
Aligning Transformers with Continuous Feedback via Energy Rank Alignment
Shriram Chennakesavalu, Frank Hu, Sebastian Ibarraran +1
Searching through chemical space is an exceptionally challenging problem because the number of possible molecules grows combinatorially with the number of atoms. Large, autoregress…
Adaptive nonequilibrium design of actin-based metamaterials: fundamental and practical limits of control
Shriram Chennakesavalu, Sreekanth K. Manikandan, Frank Hu +1
The adaptive and surprising emergent properties of biological materials self-assembled in far-from-equilibrium environments serve as an inspiration for efforts to design nanomateri…