10 papers
MegaFake: A Theory-Driven Dataset of Fake News Generated by Large Language Models
Lionel Z. Wang, Ka Chung Ng, Yiming Ma +1
Fake news significantly influences decision-making processes by misleading individuals, organizations, and even governments. Large language models (LLMs), as part of generative AI,…
ConvApparel: A Benchmark Dataset and Validation Framework for User Simulators in Conversational Recommenders
Ofer Meshi, Krisztian Balog, Sally Goldman +5
The promise of LLM-based user simulators to improve conversational AI is hindered by a critical "realism gap," leading to systems that are optimized for simulated interactions, but…
Cognitive Chunking for Soft Prompts: Accelerating Compressor Learning via Block-wise Causal Masking
Guojie Liu, Yiqi Wang, Yanfeng Yang +4
Providing extensive context via prompting is vital for leveraging the capabilities of Large Language Models (LLMs). However, lengthy contexts significantly increase inference laten…
Exploring Graph Learning Tasks with Pure LLMs: A Comprehensive Benchmark and Investigation
Yuxiang Wang, Xinnan Dai, Wenqi Fan +1
In recent years, large language models (LLMs) have emerged as promising candidates for graph tasks. Many studies leverage natural language to describe graphs and apply LLMs for rea…
HV-Attack: Hierarchical Visual Attack for Multimodal Retrieval Augmented Generation
Linyin Luo, Yujuan Ding, Yunshan Ma +2
Advanced multimodal Retrieval-Augmented Generation (MRAG) techniques have been widely applied to enhance the capabilities of Large Multimodal Models (LMMs), but they also bring alo…
Rethinking Graph Domain Adaptation: A Spectral Contrastive Perspective
Haoyu Zhang, Yuxuan Cheng, Wenqi Fan +2
Graph neural networks (GNNs) have achieved remarkable success in various domains, yet they often struggle with domain adaptation due to significant structural distribution shifts a…