Cover Image

BRIDGES: Bridging Graph Modality and Large Language Models within EDA Tasks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Wei, Zou, Yang, Ellis, Christopher, Purdy, Ruben, Blanton, Shawn, Moura, José M. F.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Large Language Models (LLMs) for Electronic Design Automation (EDA)
by: Xu, Kangwei, et al.
Published: (2025)

Bridging Large Language Models and Graph Structure Learning Models for Robust Representation Learning
by: Su, Guangxin, et al.
Published: (2024)

ChatEDA: A Large Language Model Powered Autonomous Agent for EDA
by: He, Zhuolun, et al.
Published: (2023)

GSA-Forecaster: Forecasting Graph-Based Time-Dependent Data with Graph Sequence Attention
by: Li, Yang, et al.
Published: (2021)

Graph Foundation Models: Bridging Language Model Paradigms and Graph Optimization
by: Liang, Yunhao, et al.
Published: (2025)

Bridging Visualization and Optimization: Multimodal Large Language Models on Graph-Structured Combinatorial Optimization
by: Zhao, Jie, et al.
Published: (2025)

Unveiling Hidden Collaboration within Mixture-of-Experts in Large Language Models
by: Tang, Yuanbo, et al.
Published: (2025)

Are Large-Language Models Graph Algorithmic Reasoners?
by: Taylor, Alexander K, et al.
Published: (2024)

A Human-Like Reasoning Framework for Multi-Phases Planning Task with Large Language Models
by: Xie, Chengxing, et al.
Published: (2024)

EDA-Aware RTL Generation with Large Language Models
by: Islam, Mubashir ul, et al.
Published: (2024)

Exploring Large Protein Language Models in Constrained Evaluation Scenarios within the FLIP Benchmark
by: Mollon, Manuel F., et al.
Published: (2025)

On Training Large Language Models for Long-Horizon Tasks: An Empirical Study of Horizon Length
by: Kim, Sunghwan, et al.
Published: (2026)

Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs
by: Chen, Zhikai, et al.
Published: (2023)

Modality-free Graph In-context Alignment
by: Zhuo, Wei, et al.
Published: (2026)

Graph Tokenization for Bridging Graphs and Transformers
by: Guo, Zeyuan, et al.
Published: (2026)

Exploring Correlations of Self-Supervised Tasks for Graphs
by: Fang, Taoran, et al.
Published: (2024)

MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks
by: Zhang, Lei, et al.
Published: (2023)

GraphT5: Unified Molecular Graph-Language Modeling via Multi-Modal Cross-Token Attention
by: Kim, Sangyeup, et al.
Published: (2025)

Data-centric Federated Graph Learning with Large Language Models
by: Yan, Bo, et al.
Published: (2025)

Towards Harnessing the Collaborative Power of Large and Small Models for Domain Tasks
by: Liu, Yang, et al.
Published: (2025)

M2WLLM: Multi-Modal Multi-Task Ultra-Short-term Wind Power Prediction Algorithm Based on Large Language Model
by: Fana, Hang, et al.
Published: (2025)

Exploring the Potential of Large Language Models in Graph Generation
by: Yao, Yang, et al.
Published: (2024)

TAP: Two-Stage Adaptive Personalization of Multi-Task and Multi-Modal Foundation Models in Federated Learning
by: Lee, Seohyun, et al.
Published: (2025)

Cross-Modal Unlearning via Influential Neuron Path Editing in Multimodal Large Language Models
by: Li, Kunhao, et al.
Published: (2025)

GraphEdit: Large Language Models for Graph Structure Learning
by: Guo, Zirui, et al.
Published: (2024)

Test-Time Training on Graphs with Large Language Models (LLMs)
by: Zhang, Jiaxin, et al.
Published: (2024)

A Survey of Large Language Models for Graphs
by: Ren, Xubin, et al.
Published: (2024)

Are Large Language Models In-Context Graph Learners?
by: Li, Jintang, et al.
Published: (2025)

Knowledge Graph Modeling-Driven Large Language Model Operating System (LLM OS) for Task Automation in Process Engineering Problem-Solving
by: Srinivas, Sakhinana Sagar, et al.
Published: (2024)

Task-Oriented GNNs Training on Large Knowledge Graphs for Accurate and Efficient Modeling
by: Abdallah, Hussein, et al.
Published: (2024)

Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness
by: Guo, Kai, et al.
Published: (2024)

Bridging the Knowledge Void: Inference-time Acquisition of Unfamiliar Programming Languages for Coding Tasks
by: Shen, Chen, et al.
Published: (2026)

LitBench: A Graph-Centric Large Language Model Benchmarking Tool For Literature Tasks
by: Varvarigos, Andreas, et al.
Published: (2026)

Exploring the Potential of Large Language Models as Predictors in Dynamic Text-Attributed Graphs
by: Lei, Runlin, et al.
Published: (2025)

Bridging the Semantic Gap for Categorical Data Clustering via Large Language Models
by: Yang, Zihua, et al.
Published: (2026)

How to Measure the Intelligence of Large Language Models?
by: Körber, Nils, et al.
Published: (2024)

Multimodal Survival Analysis with Locally Deployable Large Language Models
by: Gögl, Moritz, et al.
Published: (2026)

MergeNet: Knowledge Migration across Heterogeneous Models, Tasks, and Modalities
by: Li, Kunxi, et al.
Published: (2024)

Synergizing Large Language Models and Task-specific Models for Time Series Anomaly Detection
by: Chen, Feiyi, et al.
Published: (2025)

Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models
by: Jin, Yilun, et al.
Published: (2024)