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Found 8 papers, 5 papers with code
Word Order's Impacts: Insights from Reordering and Generation Analysis
Existing works have studied the impacts of the order of words within natural text.
ROME: Memorization Insights from Text, Probability and Hidden State in Large Language Models
Probing the memorization of large language models holds significant importance.
Word Order and World Knowledge
Word order is an important concept in natural language, and in this work, we study how word order affects the induction of world knowledge from raw text using language models.
Ered: Enhanced Text Representations with Entities and Descriptions
On the one hand, it is implicit and only model weights are paid attention to, the pre-trained entity embeddings are ignored.
TraceNet: Tracing and Locating the Key Elements in Sentiment Analysis
In this paper, we study sentiment analysis task where the outcomes are mainly contributed by a few key elements of the inputs.
KESA: A Knowledge Enhanced Approach For Sentiment Analysis
On the contrary, the second task predicts the overall sentiment polarity given the sentiment polarity of the word as prior knowledge.
D-HAN: Dynamic News Recommendation with Hierarchical Attention Network
News recommendation models often fall short in capturing users' preferences due to their static approach to user-news interactions.
Entity Concept-enhanced Few-shot Relation Extraction
Few-shot relation extraction (FSRE) is of great importance in long-tail distribution problem, especially in special domain with low-resource data.
