3 citations · 5 across the 9 of their papers we have counts for
9 papers
InvertiTune: High-Quality Data Synthesis for Cost-Effective Single-Shot Text-to-Knowledge Graph Generation
Faezeh Faez, Marzieh S. Tahaei, Yaochen Hu +4
Large Language Models (LLMs) have revolutionized the ability to understand and generate text, enabling significant progress in automatic knowledge graph construction from text (Tex…
E-CARE: An Efficient LLM-based Commonsense-Augmented Framework for E-Commerce
Ge Zhang, Rohan Deepak Ajwani, Yaochen Hu +5
Finding relevant products given a user query is pivotal to an e-commerce platform, as it can drive shopping behavior and generate revenue. The challenge lies in accurately predicti…
Reasoning on a Budget: A Survey of Adaptive and Controllable Test-Time Compute in LLMs
Mohammad Ali Alomrani, Yingxue Zhang, Derek Li +14
Large language models (LLMs) have rapidly progressed into general-purpose agents capable of solving a broad spectrum of tasks. However, current models remain inefficient at reasoni…
Mem2Ego: Empowering Vision-Language Models with Global-to-Ego Memory for Long-Horizon Embodied Navigation
Lingfeng Zhang, Yuecheng Liu, Zhanguang Zhang +19
Recent advancements in Large Language Models (LLMs) and Vision-Language Models (VLMs) have made them powerful tools in embodied navigation, enabling agents to leverage commonsense…
SpatialCoT: Advancing Spatial Reasoning through Coordinate Alignment and Chain-of-Thought for Embodied Task Planning
Yuecheng Liu, Dafeng Chi, Shiguang Wu +13
Spatial reasoning is an essential problem in embodied AI research. Efforts to enhance spatial reasoning abilities through supplementary spatial data and fine-tuning have proven lim…
Extracting and Following Paths for Robust Relational Reasoning with Large Language Models
Ge Zhang, Mohammad Ali Alomrani, Hongjian Gu +7
Large language models (LLMs) possess vast semantic knowledge but often struggle with complex reasoning tasks, particularly in relational reasoning problems such as kinship or spati…
Enhancing CTR Prediction in Recommendation Domain with Search Query Representation
Yuening Wang, Man Chen, Yaochen Hu +5
Many platforms, such as e-commerce websites, offer both search and recommendation services simultaneously to better meet users' diverse needs. Recommendation services suggest items…
Sparse Decomposition of Graph Neural Networks
Yaochen Hu, Mai Zeng, Ge Zhang +4
Graph Neural Networks (GNN) exhibit superior performance in graph representation learning, but their inference cost can be high, due to an aggregation operation that can require a…
Enhancing Logical Reasoning in Large Language Models through Graph-based Synthetic Data
Jiaming Zhou, Abbas Ghaddar, Ge Zhang +7
Despite recent advances in training and prompting strategies for Large Language Models (LLMs), these models continue to face challenges with complex logical reasoning tasks that in…