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Found 15 papers, 6 papers with code
DiaASQ : A Benchmark of Conversational Aspect-based Sentiment Quadruple Analysis
In this work, we introduce a novel task of conversational aspect-based sentiment quadruple analysis, namely DiaASQ, aiming to detect the sentiment quadruple of target-aspect-opinion-sentiment in a dialogue.
Conversation Disentanglement with Bi-Level Contrastive Learning
Conversation disentanglement aims to group utterances into detached sessions, which is a fundamental task in processing multi-party conversations.
Structured and Natural Responses Co-generation for Conversational Search
Existing approaches either 1) predict structured dialog acts first and then generate natural response; or 2) map conversation context to natural responses directly in an end-to-end manner.
Decoupling Strategy and Surface Realization for Task-oriented Dialogues
The core is to construct a latent content space for strategy optimization and disentangle the surface style from it.
Reproducibility Companion Paper: Knowledge Enhanced Neural Fashion Trend Forecasting
This companion paper supports the replication of the fashion trend forecasting experiments with the KERN (Knowledge Enhanced Recurrent Network) method that we presented in the ICMR 2020.
Leveraging Multiple Relations for Fashion Trend Forecasting Based on Social Media
Towards insightful fashion trend forecasting, previous work [1] proposed to analyze more fine-grained fashion elements which can informatively reveal fashion trends.
Rethinking Dialogue State Tracking with Reasoning
Tracking dialogue states to better interpret user goals and feed downstream policy learning is a bottleneck in dialogue management.
Knowledge Enhanced Neural Fashion Trend Forecasting
Further-more, to effectively model the time series data of fashion elements with rather complex patterns, we propose a Knowledge EnhancedRecurrent Network model (KERN) which takes advantage of the capability of deep recurrent neural networks in modeling time-series data.
Learning Goal-oriented Dialogue Policy with Opposite Agent Awareness
Most existing approaches for goal-oriented dialogue policy learning used reinforcement learning, which focuses on the target agent policy and simply treat the opposite agent policy as part of the environment.
Automatic Fashion Knowledge Extraction from Social Media
Fashion knowledge plays a pivotal role in helping people in their dressing.
Who, Where, and What to Wear? Extracting Fashion Knowledge from Social Media
We unify three tasks of occasion, person and clothing discovery from multiple modalities of images, texts and metadata.
Deep Conversational Recommender in Travel
When traveling to a foreign country, we are often in dire need of an intelligent conversational agent to provide instant and informative responses to our various queries.
Neural Collaborative Filtering
When it comes to model the key factor in collaborative filtering -- the interaction between user and item features, they still resorted to matrix factorization and applied an inner product on the latent features of users and items.
Attributed Social Network Embedding
For social networks, besides the network structure, there also exists rich information about social actors, such as user profiles of friendship networks and textual content of citation networks.
Social and Information Networks
