5 papers
Aligning Reasoning LLMs for Materials Discovery with Physics-aware Rejection Sampling
Lee Hyun, Sohee Yoon, Jinwoo Park +11
AI-driven materials discovery that couples automated experimentation with algorithmic decision-making requires process aware recipe to property predictors that are accurate, calibr…
ReviewScore: Misinformed Peer Review Detection with Large Language Models
Hyun Ryu, Doohyuk Jang, Hyemin S. Lee +16
Peer review serves as a backbone of academic research, but in most AI conferences, the review quality is degrading as the number of submissions explodes. To reliably detect low-qua…
Robust Molecular Property Prediction via Densifying Scarce Labeled Data
Jina Kim, Jeffrey Willette, Bruno Andreis +1
A widely recognized limitation of molecular prediction models is their reliance on structures observed in the training data, resulting in poor generalization to out-of-distribution…
A Training-free Sub-quadratic Cost Transformer Model Serving Framework With Hierarchically Pruned Attention
Heejun Lee, Geon Park, Youngwan Lee +7
In modern large language models (LLMs), increasing the context length is crucial for improving comprehension and coherence in long-context, multi-modal, and retrieval-augmented lan…
SEA: Sparse Linear Attention with Estimated Attention Mask
Heejun Lee, Jina Kim, Jeffrey Willette +1
The transformer architecture has driven breakthroughs in recent years on tasks which require modeling pairwise relationships between sequential elements, as is the case in natural…