Legal judgment prediction (LJP) is a significant task in legal intelligence, which aims to
assist the judges and determine the judgment result based on the case's fact description …

We introduce GenDecider, a novel re-ranking approach for Zero-Shot Entity Linking (ZSEL),
built on the Llama model. It innovatively detects scenarios where the correct entity is not …

Dense retrieval is widely used for entity linking to retrieve entities from large-scale
knowledge bases. Mainstream techniques are based on a dual-encoder framework, which …

Background The main task of medical entity disambiguation is to link mentions, such as
diseases, drugs, or complications, to standard entities in the target knowledge base. To our …

A common retrieve-and-rerank paradigm involves retrieving relevant candidates from a
broad set using a fast bi-encoder (BE), followed by applying expensive but accurate cross …

Zero-shot entity linking (EL) aims at aligning entity mentions to unseen entities to challenge
the generalization ability. Previous methods largely focus on the candidate retrieval stage …

Neural entity-linking models excel at bridging the lexical gap of multiple facets of facts, such
as entity-related claims or evidence documents. Despite advancements in self-supervised …

Cross-encoder models, which jointly encode and score a query-item pair, are prohibitively
expensive for direct k-nearest neighbor (k-NN) search. Consequently, k-NN search typically …

In this information-accumulating world, each of us must learn continuously. To participate in
a new field, or even a sub-field, one must be aware of the terminology including the …

A recent advancement in the domain of biomedical Entity Linking is the development of
powerful two-stage algorithms, an initial candidate retrieval stage that generates a shortlist …