4 accepted papers
Large language models (LLMs) have demonstrated impressive capabilities in various language-based reasoning tasks (e.g., math reasoning). Among all LLM reasoning frameworks, _multi-agent debate_ (MAD), which employs multiple LLM agents and performs reasoning in the way of multi-round debate, has emer…
In this paper, we address the challenge of accurately modeling and predicting Gibbs free energy in solute-solvent interactions, a pivotal yet complex aspect in the field of chemical modeling. Traditional approaches, primarily relying on deep learning models, face limitations in capturing the intrica…
Protein-protein interactions (PPIs) are crucial in various biological processes and their study has significant implications for drug development and disease diagnosis. Existing deep learning methods suffer from significant performance degradation under complex real-world scenarios due to various fa…
Pre-training on time series poses a unique challenge due to the potential mismatch between pre-training and target domains, such as shifts in temporal dynamics, fast-evolving trends, and long-range and short-cyclic effects, which can lead to poor downstream performance. While domain adaptation metho…