From the 1 of 12 linked papers with an AI index.
12 papers
Edge Sparsification via Temporal Forman-Ricci Curvature for Dynamic Graph Learning
Poupak Azad, Cuneyt Gurcan Akcora, Kiarash Shamsi
Temporal graph learning has become essential for analyzing real-world systems whose interactions continuously evolve over time, including financial transaction networks, communicat…
TopoFormer: Topology Meets Attention for Graph Learning
Md Joshem Uddin, Astrit Tola, Cuneyt Gurcan Akcora +1
The paper introduces TopoFormer, a framework that converts graph topology into ordered token sequences via a Topo-Scan module and processes them with a Transformer to obtain effici…
TopoTuner: Topological Finetuning of Large Language Models
Abdulkadir Erol, Yash Mahajan, Vepaul Hariprashad +4
Full fine-tuning remains a strong way to adapt pretrained LLMs, but it updates all weights and can be expensive. LoRA reduces the number of trainable parameters, but it does not di…
The Illusion of Equivalency: Statistical Characterization of Quantization Effects in LLMs
Baha Rababah, Cuneyt Gurcan Akcora, Shahzeb Qamar +4
Post-Training Quantization has become widely used to compress large language models to make them deployable on resource-constrained devices. However, the evaluation of quantization…
Optimal Transport-Guided Adversarial Attacks on Graph Neural Network-Based Bot Detection
Kunal Mukherjee, Zulfikar Alom, Tran Gia Bao Ngo +2
The rise of bot accounts on social media poses significant risks to public discourse. To address this threat, modern bot detectors increasingly rely on Graph Neural Networks (GNNs)…
Adversarial Graph Neural Network Benchmarks: Towards Practical and Fair Evaluation
Tran Gia Bao Ngo, Zulfikar Alom, Federico Errica +2
Adversarial learning and the robustness of Graph Neural Networks (GNNs) are topics of widespread interest in the machine learning community, as documented by the number of adversar…