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Found 13 papers, 2 papers with code
Exploiting Document Level Information to Improve Event Detection via Recurrent Neural Networks
This paper tackles the task of event detection, which involves identifying and categorizing events.
Implicit Discourse Relation Recognition using Neural Tensor Network with Interactive Attention and Sparse Learning
In this paper, we propose a novel neural Tensor network framework with Interactive Attention and Sparse Learning (TIASL) for implicit discourse relation recognition.
Interaction-Aware Topic Model for Microblog Conversations through Network Embedding and User Attention
They ignore that one discusses diverse topics when dynamically interacting with different people.
A Semi-Supervised Stable Variational Network for Promoting Replier-Consistency in Dialogue Generation
However, the sampled information from latent space usually becomes useless due to the KL divergence vanishing issue, and the highly abstractive global variables easily dilute the personal features of replier, leading to a non replier-specific response.
TransS-Driven Joint Learning Architecture for Implicit Discourse Relation Recognition
Implicit discourse relation recognition is a challenging task due to the lack of connectives as strong linguistic clues.
TWEETSUM: Event oriented Social Summarization Dataset
In this paper, we construct TWEETSUM, a new event-oriented dataset for social summarization.
Aligning Recommendation and Conversation via Dual Imitation
Human conversations of recommendation naturally involve the shift of interests which can align the recommendation actions and conversation process to make accurate recommendations with rich explanations.
Enhancing Personalized Dialogue Generation with Contrastive Latent Variables: Combining Sparse and Dense Persona
We design a Contrastive Latent Variable-based model (CLV) that clusters the dense persona descriptions into sparse categories, which are combined with the history query to generate personalized responses.
Mind vs. Mouth: On Measuring Re-judge Inconsistency of Social Bias in Large Language Models
We propose that this re-judge inconsistency can be similar to the inconsistency between human's unaware implicit social bias and their aware explicit social bias.
Infusing Hierarchical Guidance into Prompt Tuning: A Parameter-Efficient Framework for Multi-level Implicit Discourse Relation Recognition
First, we leverage parameter-efficient prompt tuning to drive the inputted arguments to match the pre-trained space and realize the approximation with few parameters.
CRFR: Improving Conversational Recommender Systems via Flexible Fragments Reasoning on Knowledge Graphs
Although paths of user interests shift in knowledge graphs (KGs) can benefit conversational recommender systems (CRS), explicit reasoning on KGs has not been well considered in CRS, due to the complex of high-order and incomplete paths.
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CR-GIS: Improving Conversational Recommendation via Goal-aware Interest Sequence Modeling
In CRS, implicit patterns of user interest sequence guide the smooth transition of dialog utterances to the goal item.
TopKG: Target-oriented Dialog via Global Planning on Knowledge Graph
We design a global reinforcement learning with the planned paths to flexibly adjust the local response generation model towards the global target.
