9 citations · 9 across the 6 of their papers we have counts for
8 papers
Soft Ontology Priors over Latent Concept Posteriors for Weakly Supervised Neuro-Symbolic Learning
Tengwei Song, Robert Hoehndorf
Neuro-symbolic (NeSy) predictors that supervise only the task label suffer from reasoning shortcuts: distinct concept mappings achieve the same maximum likelihood, leaving the reco…
MemPlan: Memory-Conditioned PDDL Planning for Partially Observable Text Environments
Tengwei Song, Robert Hoehndorf
LLM agents are flexible in language interaction, but using them as long-horizon planners is costly and prone to hallucinated or invalid actions. This paper targets a different role…
Improving Enzyme Prediction with Chemical Reaction Equations by Hypergraph-Enhanced Knowledge Graph Embeddings
Tengwei Song, Long Yin, Zhen Han +1
Predicting enzyme-substrate interactions has long been a fundamental problem in biochemistry and metabolic engineering. While existing methods could leverage databases of expert-cu…
Unified Molecule Pre-training with Flexible 2D and 3D Modalities: Single and Paired Modality Integration
Tengwei Song, Min Wu, Yuan Fang
Molecular representation learning plays a crucial role in advancing applications such as drug discovery and material design. Existing work leverages 2D and 3D modalities of molecul…
MusiXQA: Advancing Visual Music Understanding in Multimodal Large Language Models
Jian Chen, Wenye Ma, Penghang Liu +7
Multimodal Large Language Models (MLLMs) have achieved remarkable visual reasoning abilities in natural images, text-rich documents, and graphic designs. However, their ability to…
Robust Knowledge Graph Embedding via Denoising
Tengwei Song, Xudong Ma, Yang Liu +1
We focus on obtaining robust knowledge graph embedding under perturbation in the embedding space. To address these challenges, we introduce a novel framework, Robust Knowledge Grap…
Modulate Your Spectrum in Self-Supervised Learning
Xi Weng, Yunhao Ni, Tengwei Song +5
Whitening loss offers a theoretical guarantee against feature collapse in self-supervised learning (SSL) with joint embedding architectures. Typically, it involves a hard whitening…
Rot-Pro: Modeling Transitivity by Projection in Knowledge Graph Embedding
Tengwei Song, Jie Luo, Lei Huang
Knowledge graph embedding models learn the representations of entities and relations in the knowledge graphs for predicting missing links (relations) between entities. Their effect…