2 papers
cs.CL2025
From Sequence to Structure: Uncovering Substructure Reasoning in Transformers
Xinnan Dai, Kai Yang, Jay Revolinsky +4
Recent studies suggest that large language models (LLMs) possess the capability to solve graph reasoning tasks. Notably, even when graph structures are embedded within textual desc…
cs.LG2024
How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension
Xinnan Dai, Haohao Qu, Yifen Shen +6
Benchmarking the capabilities and limitations of large language models (LLMs) in graph-related tasks is becoming an increasingly popular and crucial area of research. Recent studie…