Entity alignment (EA) is a fundamental data integration task that identifies equivalent entities
between different knowledge graphs (KGs). Temporal Knowledge graphs (TKGs) extend …

Maximizing the user-item engagement based on vectorized embeddings is a standard
procedure of recent recommender models. Despite the superior performance for item …

We propose the first character-level white-box adversarial attack method against transformer
models. The intuition of our method comes from the observation that words are split into …

How can we better extract entities and relations from text? Using multimodal extraction with
images and text obtains more signals for entities and relations, and aligns them through …

The generalizability to new databases is of vital importance to Text-to-SQL systems which
aim to parse human utterances into SQL statements. Existing works achieve this goal by …

Multimodal relation extraction (MRE) is the task of identifying the semantic relationships
between two entities based on the context of the sentence image pair. Existing retrieval …

Relation extraction (RE) tasks show promising performance in extracting relations from two
entities mentioned in sentences, given sufficient annotations available during training. Such …

Real-world fact verification task aims to verify the factuality of a claim by retrieving evidence
from the source document. The quality of the retrieved evidence plays an important role in …

How to identify semantic relations among entities in a document when only a few labeled
documents are available? Few-shot document-level relation extraction (FSDLRE) is crucial …

Data augmentation techniques have been used to alleviate the problem of scarce labeled
data in various NER tasks (flat, nested, and discontinuous NER tasks). Existing …