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Found 7 papers, 5 papers with code
Optimal Partial Transport Based Sentence Selection for Long-form Document Matching
Enjoying the partial transport properties of OPT, the selected key sentences can not only effectively enhance the matching accuracy, but also be explained as the rationales for the matching results.
Logic Rules as Explanations for Legal Case Retrieval
In this paper, we address the issue of using logic rules to explain the results from legal case retrieval.
UOEP: User-Oriented Exploration Policy for Enhancing Long-Term User Experiences in Recommender Systems
Reinforcement learning (RL) has gained traction for enhancing user long-term experiences in recommender systems by effectively exploring users' interests.
Explicitly Integrating Judgment Prediction with Legal Document Retrieval: A Law-Guided Generative Approach
Legal document retrieval and judgment prediction are crucial tasks in intelligent legal systems.
Uncovering ChatGPT's Capabilities in Recommender Systems
The debut of ChatGPT has recently attracted the attention of the natural language processing (NLP) community and beyond.
Explainable Legal Case Matching via Inverse Optimal Transport-based Rationale Extraction
As an essential operation of legal retrieval, legal case matching plays a central role in intelligent legal systems.
Wasserstein Distance Regularized Sequence Representation for Text Matching in Asymmetrical Domains
Four popular text matching methods have been exploited in the paper.
