Fu Zhang

Although camouflaged object segmentation has advanced rapidly in recent years, existing methods are still confined to visual mask prediction under fixed task assumptions. They cannot interactively respond to user requests, nor can they proactively understand and reason about the user’s intent. Ou...

Cross-document Relation Extraction (CodRE) requires reasoning over scattered evidence to identify relations between target entities across multiple documents. Existing methods indiscriminately fuse target entities and the intermediate bridge entities that link them into a unified representation....

Guqin (古琴) Jianzi (減字) is an open and freely compositional tablature system that encodes performance actions rather than acoustic outcomes. Its automatic recognition remains largely unexplored, as conventional OCR assumes a closed and enumerable glyph set and struggles with Jianzi’s unbounded com...

Document-level relation extraction (DocRE) aims to determine which relations hold between a given entity pair within a document. As a multi-label classification task, the most commonly adopted paradigm introduces a learnable threshold to distinguish positive and negative classes for an entity pai...

Multi-modal Knowledge Graph Completion (MKGC) aims to infer missing links in multimodal knowledge graphs by leveraging structured triples together with auxiliary modalities such as text and images. Existing MKGC methods typically train with all modalities available, implicitly assuming consistent...

Temporal knowledge graph (TKG) forecasting aims to infer future facts from historical observations in time-evolving graphs. Traditional rule-based methods often rely on statistical co-occurrences and extensive path enumeration, suffering from rule sparsity and search-space explosion, while recent...

Zero-Shot Relation Extraction (ZSRE) aims to predict unseen relations for given entity pairs in sentences. Existing methods typically operate from a local perspective, predicting the relation for each entity pair (given its corresponding sentence) in isolation. Consequently, they often fail to di...

Multi-interest recommendation is essential for the matching stage. By generating multiple user representations, it can better cover the diverse interests derived from user interaction history. Ideally, multi-interest models should effectively identify the underlying latent factors — the specific...