Search Results for author:
Found 11 papers, 5 papers with code
DELTA: Pre-train a Discriminative Encoder for Legal Case Retrieval via Structural Word Alignment
Most of the existing works focus on improving the representation ability for the contextualized embedding of the [CLS] token and calculate relevance using textual semantic similarity.
BLADE: Enhancing Black-box Large Language Models with Small Domain-Specific Models
However, general LLMs, which are developed on open-domain data, may lack the domain-specific knowledge essential for tasks in vertical domains, such as legal, medical, etc.
Unsupervised Large Language Model Alignment for Information Retrieval via Contrastive Feedback
Large language models (LLMs) have demonstrated remarkable capabilities across various research domains, including the field of Information Retrieval (IR).
I^3 Retriever: Incorporating Implicit Interaction in Pre-trained Language Models for Passage Retrieval
Moreover, the proposed implicit interaction is compatible with special pre-training and knowledge distillation for passage retrieval, which brings a new state-of-the-art performance.
SAILER: Structure-aware Pre-trained Language Model for Legal Case Retrieval
Moreover, in contrast to the general retrieval, the relevance in the legal domain is sensitive to key legal elements.
T2Ranking: A large-scale Chinese Benchmark for Passage Ranking
T2Ranking comprises more than 300K queries and over 2M unique passages from real-world search engines.
Social4Rec: Distilling User Preference from Social Graph for Video Recommendation in Tencent
Despite recommender systems play a key role in network content platforms, mining the user's interests is still a significant challenge.
Layout-aware Webpage Quality Assessment
To assess webpage quality from complex DOM tree data, we propose a graph neural network (GNN) based method that extracts rich layout-aware information that implies webpage quality in an end-to-end manner.
Incorporating Explicit Knowledge in Pre-trained Language Models for Passage Re-ranking
To leverage a reliable knowledge, we propose a novel knowledge graph distillation method and obtain a knowledge meta graph as the bridge between query and passage.
Perspective, Survey and Trends: Public Driving Datasets and Toolsets for Autonomous Driving Virtual Test
To the best of our knowledge, we are the first to perform such recent empirical survey on both the datasets and toolsets using a SLA based survey approach.
JIT-Masker: Efficient Online Distillation for Background Matting
We design a real-time portrait matting pipeline for everyday use, particularly for "virtual backgrounds" in video conferences.
