35 citations · 39 across the 18 of their papers we have counts for
5 papers · 1 filter
Tracing Morphology, Semantics, and Divergence in Language Acquisition
Forough Shirin Abkenar, Haoshuo Fu, Liang Feng +2
Understanding the dynamics of language acquisition in Large Language Models (LLMs) is crucial for uncovering how statistical representations evolve into structured linguistic capab…
CORE: Constraint-Aware One-Step Reinforcement Learning for Simulation-Guided Neural Network Accelerator Design
Yifeng Xiao, Yurong Xu, Ning Yan +2
Simulation-based design space exploration (DSE) aims to efficiently optimize high-dimensional structured designs under complex constraints and expensive evaluation costs. Existing…
LLM-driven Knowledge Distillation for Dynamic Text-Attributed Graphs
Amit Roy, Ning Yan, Masood Mortazavi
Dynamic Text-Attributed Graphs (DyTAGs) have numerous real-world applications, e.g. social, collaboration, citation, communication, and review networks. In these networks, nodes an…
HetGPT: Harnessing the Power of Prompt Tuning in Pre-Trained Heterogeneous Graph Neural Networks
Yihong Ma, Ning Yan, Jiayu Li +2
Graphs have emerged as a natural choice to represent and analyze the intricate patterns and rich information of the Web, enabling applications such as online page classification an…
Theta-Resonance: A Single-Step Reinforcement Learning Method for Design Space Exploration
Masood S. Mortazavi, Tiancheng Qin, Ning Yan
Given an environment (e.g., a simulator) for evaluating samples in a specified design space and a set of weighted evaluation metrics -- one can use Theta-Resonance, a single-step M…