19 citations · 32 across the 7 of their papers we have counts for
8 papers
ESG-Bench: Benchmarking Long-Context ESG Reports for Hallucination Mitigation
Siqi Sun, Ben Peng Wu, Mali Jin +3
As corporate responsibility increasingly incorporates environmental, social, and governance (ESG) criteria, ESG reporting is becoming a legal requirement in many regions and a key…
Towards deployment-centric multimodal AI beyond vision and language
Xianyuan Liu, Jiayang Zhang, Shuo Zhou +45
Multimodal artificial intelligence (AI) integrates diverse types of data via machine learning to improve understanding, prediction, and decision-making across disciplines such as h…
Mask prior-guided denoising diffusion improves inverse protein folding
Peizhen Bai, Filip Miljković, Xianyuan Liu +4
Inverse protein folding generates valid amino acid sequences that can fold into a desired protein structure, with recent deep-learning advances showing strong potential and competi…
Addressing Topic Granularity and Hallucination in Large Language Models for Topic Modelling
Yida Mu, Peizhen Bai, Kalina Bontcheva +1
Large language models (LLMs) with their strong zero-shot topic extraction capabilities offer an alternative to probabilistic topic modelling and closed-set topic classification app…
Geometry-aware Line Graph Transformer Pre-training for Molecular Property Prediction
Peizhen Bai, Xianyuan Liu, Haiping Lu
Molecular property prediction with deep learning has gained much attention over the past years. Owing to the scarcity of labeled molecules, there has been growing interest in self-…
Interpretable bilinear attention network with domain adaptation improves drug-target prediction
Peizhen Bai, Filip Miljković, Bino John +1
Predicting drug-target interaction is key for drug discovery. Recent deep learning-based methods show promising performance but two challenges remain: (i) how to explicitly model a…
PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python
Haiping Lu, Xianyuan Liu, Robert Turner +5
Machine learning is a general-purpose technology holding promises for many interdisciplinary research problems. However, significant barriers exist in crossing disciplinary boundar…
GripNet: Graph Information Propagation on Supergraph for Heterogeneous Graphs
Hao Xu, Shengqi Sang, Peizhen Bai +2
Heterogeneous graph representation learning aims to learn low-dimensional vector representations of different types of entities and relations to empower downstream tasks. Existing…