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Found 20 papers, 1 papers with code
Task-Completion Dialogue Policy Learning via Monte Carlo Tree Search with Dueling Network
We introduce a framework of Monte Carlo Tree Search with Double-q Dueling network (MCTS-DDU) for task-completion dialogue policy learning.
Model-based Reinforcement Learning
reinforcement-learning
+2
A Diversity-Enhanced and Constraints-Relaxed Augmentation for Low-Resource Classification
Previous studies mostly use a fine-tuned Language Model (LM) to strengthen the constraints but ignore the fact that the potential of diversity could improve the effectiveness of generated data.
FPAI at SemEval-2021 Task 6: BERT-MRC for Propaganda Techniques Detection
The objective of subtask 2 of SemEval-2021 Task 6 is to identify techniques used together with the span(s) of text covered by each technique.
RG PA at SemEval-2021 Task 1: A Contextual Attention-based Model with RoBERTa for Lexical Complexity Prediction
In this paper we propose a contextual attention based model with two-stage fine-tune training using RoBERTa.
RefBERT: Compressing BERT by Referencing to Pre-computed Representations
Differently, in this paper, we propose RefBERT to leverage the knowledge learned from the teacher, i. e., facilitating the pre-computed BERT representation on the reference sample and compressing BERT into a smaller student model.
Progressive Open-Domain Response Generation with Multiple Controllable Attributes
More specifically, PHED deploys Conditional Variational AutoEncoder (CVAE) on Transformer to include one aspect of attributes at one stage.
PALI at SemEval-2021 Task 2: Fine-Tune XLM-RoBERTa for Word in Context Disambiguation
Second, we construct a new vector on the fine-tuned embeddings from XLM-RoBERTa and feed it to a fully-connected network to output the probability of whether the target word in the context has the same meaning or not.
Emotion Dynamics Modeling via BERT
Emotion dynamics modeling is a significant task in emotion recognition in conversation.
KGSynNet: A Novel Entity Synonyms Discovery Framework with Knowledge Graph
Entity synonyms discovery is crucial for entity-leveraging applications.
Automatic Intent-Slot Induction for Dialogue Systems
Automatically and accurately identifying user intents and filling the associated slots from their spoken language are critical to the success of dialogue systems.
Mention Extraction and Linking for SQL Query Generation
On the WikiSQL benchmark, state-of-the-art text-to-SQL systems typically take a slot-filling approach by building several dedicated models for each type of slots.
XSYSIGMA at SemEval-2020 Task 7: Method for Predicting Headlines' Humor Based on Auxiliary Sentences with EI-BERT
In this paper, we only report our implement of Subtask 2.
FPAI at SemEval-2020 Task 10: A Query Enhanced Model with RoBERTa for Emphasis Selection
This paper describes the model we apply in the SemEval-2020 Task 10.
FASTMATCH: Accelerating the Inference of BERT-based Text Matching
Recently, pre-trained language models such as BERT have shown state-of-the-art accuracies in text matching.
UNIXLONG at SemEval-2020 Task 6: A Joint Model for Definition Extraction
The goal of this task is to extract definition, word level BIO tags and relations.
SQL Generation via Machine Reading Comprehension
Text-to-SQL systems offers natural language interfaces to databases, which can automatically generates SQL queries given natural language questions.
Make Templates Smarter: A Template Based Data2Text System Powered by Text Stitch Model
In addition, it reduces human involvement in template design by using a text stitch model to automatically stitch adjacent template units, which is a step that usually requires careful template design and limits template reusability.
DialogueTRM: Exploring the Intra- and Inter-Modal Emotional Behaviors in the Conversation
Emotion Recognition in Conversations (ERC) is essential for building empathetic human-machine systems.
Hierarchical Context Enhanced Multi-Domain Dialogue System for Multi-domain Task Completion
Task 1 of the DSTC8-track1 challenge aims to develop an end-to-end multi-domain dialogue system to accomplish complex users' goals under tourist information desk settings.
An End-to-End Dialogue State Tracking System with Machine Reading Comprehension and Wide & Deep Classification
This paper describes our approach in DSTC 8 Track 4: Schema-Guided Dialogue State Tracking.
