collaborators

6 papers

cs.IR2026

TimeRoute: Time-Aware Modality Routing and Diffusion for Multi-Modal Recommendation

Pengyu Zhang, Yangqin Jiang, Klim Zaporojets +2

Multi-modal recommenders fuse collaborative signals with item modalities such as text, images, and audio, but the usefulness of each drifts over time and at different rates. For ex…

cs.CV2026

Time Imprint: Learning Time-Aware Representations in Multi-Modal Knowledge Graphs

Pengyu Zhang, Klim Zaporojets, Congfeng Cao +2

Multi-Modal Knowledge Graphs (MMKGs) enrich entities with multiple modalities such as text and images, yet entities with highly similar multi-modal features remain difficult to dis…

cs.CL2026

EMERGE: A Benchmark for Updating Knowledge Graphs with Emerging Textual Knowledge

Klim Zaporojets, Daniel Daza, Edoardo Barba +3

Knowledge Graphs (KGs) are structured knowledge repositories containing entities and relations between them. In this paper, we study the problem of automatically updating KGs over…

cs.CV2026

Are a Thousand Words Better Than a Single Picture? Beyond Images -- A Framework for Multi-Modal Knowledge Graph Dataset Enrichment

Pengyu Zhang, Klim Zaporojets, Jie Liu +2

Multi-Modal Knowledge Graphs (MMKGs) benefit from visual information, yet large-scale image collection is hard to curate and often excludes ambiguous but relevant visuals (e.g., lo…

cs.LG2025

A Survey of Large Language Models for Data Challenges in Graphs

Mengran Li, Pengyu Zhang, Wenbin Xing +11

Graphs are a widely used paradigm for representing non-Euclidean data, with applications ranging from social network analysis to biomolecular prediction. While graph learning has a…

cs.CL2025

Influences on LLM Calibration: A Study of Response Agreement, Loss Functions, and Prompt Styles

Yuxi Xia, Pedro Henrique Luz de Araujo, Klim Zaporojets +1

Calibration, the alignment between model confidence and prediction accuracy, is critical for the reliable deployment of large language models (LLMs). Existing works neglect to meas…