The results of information retrieval (IR) are usually presented in the form of a ranking list of
candidate documents, such as web search for humans and retrieval-augmented generation …

Recent years have seen increasing attention on Legal Case Retrieval (LCR), a key task in
the area of Legal AI that concerns the retrieval of cases from a large legal database of …

We study ranked list truncation (RLT) from a novel retrieve-then-re-rank perspective, where
we optimize re-ranking by truncating the retrieved list (ie, trim re-ranking candidates). RLT is …

Verifying the facts alleged by the prosecutors before the trial requires the judges to retrieve
evidence within the massive materials accompanied. Existing Legal AI applications often …

Legal case retrieval plays an important role for legal practitioners to effectively retrieve
relevant cases given a query case. Most existing neural legal case retrieval models directly …

In case law, the precedents are the relevant cases that are used to support the decisions
made by the judges and the opinions of lawyers towards a given case. This relevance is …

Legal case retrieval is an information retrieval task in the legal domain, which aims to
retrieve relevant cases with a given query case. Recent research of legal case retrieval …

In this paper, we investigate the task of response ranking in conversational legal search. We
propose a novel method for conversational passage response retrieval (ConvPR) for long …

In embedding-based retrieval, Approximate Nearest Neighbor (ANN) search enables
efficient retrieval of similar items from large-scale datasets. While maximizing recall of …

The conventional top-K recommendation, which presents the top-K items with the highest
ranking scores, is a common practice for generating personalized ranking lists. However, is …