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Found 5 papers, 1 papers with code
Dynamic Sub-graph Distillation for Robust Semi-supervised Continual Learning
In this work, we focus on semi-supervised continual learning (SSCL), where the model progressively learns from partially labeled data with unknown categories.
Improving Factual Consistency of Text Summarization by Adversarially Decoupling Comprehension and Embellishment Abilities of LLMs
Despite the recent progress in text summarization made by large language models (LLMs), they often generate summaries that are factually inconsistent with original articles, known as "hallucinations" in text generation.
U-NEED: A Fine-grained Dataset for User Needs-Centric E-commerce Conversational Recommendation
In this paper, we construct a user needs-centric E-commerce conversational recommendation dataset (U-NEED) from real-world E-commerce scenarios.
Exploratory Neural Relation Classification for Domain Knowledge Acquisition
The goal is to learn a classifier on pre-defined relations and discover new relations expressed in texts.
Learning Fine-grained Relations from Chinese User Generated Categories
User generated categories (UGCs) are short texts that reflect how people describe and organize entities, expressing rich semantic relations implicitly.
