17 citations · 33 across the 9 of their papers we have counts for
9 papers
Improving Language Agents through BREW: Bootstrapping expeRientially-learned Environmental knoWledge
Shashank Kirtania, Param Biyani, Priyanshu Gupta +4
Large Language Model (LLM)-based agents are increasingly capable of complex, multi-step tasks such as GUI automation, tool use, and data manipulation, yet they cannot learn from ex…
Non-Euclidean Mixture Model for Social Network Embedding
Roshni G. Iyer, Yewen Wang, Wei Wang +1
It is largely agreed that social network links are formed due to either homophily or social influence. Inspired by this, we aim at understanding the generation of links via providi…
MolX: Enhancing Large Language Models for Molecular Understanding With A Multi-Modal Extension
Khiem Le, Zhichun Guo, Kaiwen Dong +8
Large Language Models (LLMs) with their strong task-handling capabilities have shown remarkable advancements across a spectrum of fields, moving beyond natural language understandi…
Hierarchical Attention Models for Multi-Relational Graphs
Roshni G. Iyer, Wei Wang, Yizhou Sun
We present Bi-Level Attention-Based Relational Graph Convolutional Networks (BR-GCN), unique neural network architectures that utilize masked self-attentional layers with relationa…
Bi-Level Attention Graph Neural Networks
Roshni G. Iyer, Wei Wang, Yizhou Sun
Recent graph neural networks (GNNs) with the attention mechanism have historically been limited to small-scale homogeneous graphs (HoGs). However, GNNs handling heterogeneous graph…
Dual-Geometric Space Embedding Model for Two-View Knowledge Graphs
Roshni G. Iyer, Yunsheng Bai, Wei Wang +1
Two-view knowledge graphs (KGs) jointly represent two components: an ontology view for abstract and commonsense concepts, and an instance view for specific entities that are instan…
Graph-based Molecular Representation Learning
Zhichun Guo, Kehan Guo, Bozhao Nan +8
Molecular representation learning (MRL) is a key step to build the connection between machine learning and chemical science. In particular, it encodes molecules as numerical vector…
Question-Answer Sentence Graph for Joint Modeling Answer Selection
Roshni G. Iyer, Thuy Vu, Alessandro Moschitti +1
This research studies graph-based approaches for Answer Sentence Selection (AS2), an essential component for retrieval-based Question Answering (QA) systems. During offline learnin…
Software Language Comprehension using a Program-Derived Semantics Graph
Roshni G. Iyer, Yizhou Sun, Wei Wang +1
Traditional code transformation structures, such as abstract syntax trees (ASTs), conteXtual flow graphs (XFGs), and more generally, compiler intermediate representations (IRs), ma…