Ruolin Su's Projects
Open source code for EMNLP 2020 Findings Paper "AGIF: An Adaptive Graph-Interactive Framework for Joint MultipleIntent Detection and Slot Filling"
LSTM and QRNN Language Model Toolkit for PyTorch
Code for our paper "A Contextual Hierarchical Attention Network with Adaptive Objective for Dialogue State Tracking" (ACL2020)
Choice Fusion as Knowledge for Zero-Shot Dialogue State Tracking (ICASSP 2023)
A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset
Code examples in pyTorch and Tensorflow for CS230
Code for Li Zhou, Kevin Small. Multi-domain Dialogue State Tracking as Dynamic Knowledge Graph Enhanced Question Answering. In NeurIPS 2019 Workshop on Conversational AI
Code and model for the paper "Improving Language Understanding by Generative Pre-Training"
Implementation of graph-based DST with prompt adapter.
Llama from scratch, or How to implement a paper without crying
Converting data from https://github.com/budzianowski/multiwoz
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
find and download papers from acl
A framework for training and evaluating AI models on a variety of openly available dialogue datasets.
Image-to-Image Translation in PyTorch
:art: A ridiculously elegant Jekyll theme.
Overview of dialogue system for specific goals
Tasks via Dialogue in Different Service Scenarios
This is the source implementation of ACL2019 accepted paper: A Novel Bi-directional Interrelated Model for Joint Intent Detection and Slot Filling(https://www.aclweb.org/anthology/P19-1544).
slot filling, intent detection, joint training, ATIS & SNIPS datasets, MIT corpus, ELMo, BERT, XLNet
Slot-Gated Modeling for Joint Slot Filling and Intent Prediction
Open source code for EMNLP-19 Paper "A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding".
Table for INTERSPEECH 2021
This is ONLY for testing connections to Github.
Source code for transferable dialogue state generator (TRADE, Wu et al., 2019). https://arxiv.org/abs/1905.08743
š¤ Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.