An open source library for deep learning end-to-end dialog systems and chatbots.

基于金融-司法领域(兼有闲聊性质)的聊天机器人，其中的主要模块有信息抽取、NLU、NLG、知识图谱等，并且利用Django整合了前端展示,目前已经封装了nlp和kg的restful接口

A TensorFlow implementation of Recurrent Neural Networks for Sequence Classification and Sequence Labeling

slot filling, intent detection, joint training, ATIS & SNIPS datasets, the Facebook’s multilingual dataset, MIT corpus, E-commerce Shopping Assistant (ECSA) dataset, CoNLL2003 NER, ELMo, BERT, XLNet

基于pytorch的中文意图识别和槽位填充

attention based joint model for intent detection and slot filling

Few-Shot-Intent-Detection includes popular challenging intent detection datasets with/without OOS queries and state-of-the-art baselines and results.

Open source code for EMNLP-19 Paper "A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding".

Open-source ecosystem for building AI-powered conversational solutions using RAG, agents, FSMs, and LLMs.

Joint Slot Filling and Intent Detection via Capsule Neural Networks (ACL'19) https://arxiv.org/abs/1812.09471

Open source code for EMNLP 2020 Findings Paper "AGIF: An Adaptive Graph-Interactive Framework for Joint Multiple Intent Detection and Slot Filling"

BERT-based joint intent detection and slot filling with intent-slot attention mechanism (INTERSPEECH 2021)

Deep Open Intent Classification with Adaptive Decision Boundary (AAAI 2021)

MIntRec2.0 is the first large-scale dataset for multimodal intent recognition and out-of-scope detection in multi-party conversations (ICLR 2024)

Natural language understanding library for chatbots with intent recognition and entity extraction.

Automated machine learning for text classification

Implementation of Z-BERT-A: a zero-shot pipeline for unknown intent detection.

Open source code and data for AAAI 2022 Oral Paper "Text is no more Enough! A Benchmark for Profile-based Spoken Language Understanding"

[RA-L21] Long-Term Pedestrian Trajectory Prediction Using Mutable Intention Filter and Warp LSTM

MISCA: A Joint Model for Multiple Intent Detection and Slot Filling with Intent-Slot Co-Attention (EMNLP 2023 - Findings)