Cheap and reliable Node.js hosting starts at $3/month, and $1/month static HTML hosting

RNNLG is an open source benchmark toolkit for Natural Language Generation (NLG) in spoken dialogue system application domains. It is released by Tsung-Hsien (Shawn) Wen from Cambridge Dialogue Systems Group under Apache License 2.0.

Stars: ✭ 487 (-4.13%)

Mutual labels: natural-language-processing, dialogue-systems

Text mining resources

Resources for learning about Text Mining and Natural Language Processing

Stars: ✭ 358 (-29.53%)

Mutual labels: natural-language-processing, topic-modeling

Cdqa

⛔ [NOT MAINTAINED] An End-To-End Closed Domain Question Answering System.

Stars: ✭ 500 (-1.57%)

Mutual labels: question-answering, natural-language-processing

Medquad

Medical Question Answering Dataset of 47,457 QA pairs created from 12 NIH websites

Stars: ✭ 129 (-74.61%)

Mutual labels: question-answering, natural-language-processing

Clicr

Machine reading comprehension on clinical case reports

Stars: ✭ 123 (-75.79%)

Mutual labels: question-answering, natural-language-processing

Cmrc2018

A Span-Extraction Dataset for Chinese Machine Reading Comprehension (CMRC 2018)

Stars: ✭ 238 (-53.15%)

Mutual labels: question-answering, natural-language-processing

Dynamic Coattention Network Plus

Dynamic Coattention Network Plus (DCN+) TensorFlow implementation. Question answering using Deep NLP.

Stars: ✭ 117 (-76.97%)

Mutual labels: question-answering, natural-language-processing

explicit memory tracker

[ACL 2020] Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading

Stars: ✭ 35 (-93.11%)

Mutual labels: question-answering, dialogue-systems

Gnn4nlp Papers

A list of recent papers about Graph Neural Network methods applied in NLP areas.

Stars: ✭ 405 (-20.28%)

Mutual labels: question-answering, natural-language-processing

Sentence Similarity

PyTorch implementations of various deep learning models for paraphrase detection, semantic similarity, and textual entailment

Stars: ✭ 96 (-81.1%)

Mutual labels: question-answering, natural-language-processing

Neuronblocks

NLP DNN Toolkit - Building Your NLP DNN Models Like Playing Lego

Stars: ✭ 1,356 (+166.93%)

Mutual labels: question-answering, natural-language-processing

View All Similar Projects ➔

Paper-Reading

Paper reading list in natural language processing, with special emphasis on dialogue systems and text generation related topics. This repo will keep updating 🤗 ...

Paper-Reading

Deep Learning in NLP

CNM: "CNM: An Interpretable Complex-valued Network for Matching". NAACL(2019) [PDF] [code]
word2vec: "word2vec Parameter Learning Explained". arXiv(2016) [PDF] ⭐️⭐️⭐️⭐️⭐️
Glove: "GloVe: Global Vectors for Word Representation". EMNLP(2014) [PDF] [code]
ELMo: "Deep contextualized word representations". NAACL(2018) [PDF] [code]
VAE: "An Introduction to Variational Autoencoders". arXiv(2019) [PDF]
Transformer: "Attention is All you Need". NeurIPS(2017) [PDF] [code-official] [code-tf] [code-py]
Transformer-XL: "Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context". ACL(2019) [PDF] [code]
ConvS2S: "Convolutional Sequence to Sequence Learning". ICML(2017) [PDF]
Survey on Attention: "An Introductory Survey on Attention Mechanisms in NLP Problems". arXiv(2018) [PDF] ⭐️⭐️⭐️⭐️⭐️
Additive Attention: "Neural Machine Translation by Jointly Learning to Align and Translate". ICLR(2015) [PDF]
Multiplicative Attention: "Effective Approaches to Attention-based Neural Machine Translation". EMNLP(2015) [PDF]
Memory Net: "End-To-End Memory Networks". NeurIPS(2015) [PDF]
Pointer Net: "Pointer Networks". NeurIPS(2015) [PDF]
Copying Mechanism: "Incorporating Copying Mechanism in Sequence-to-Sequence Learning". ACL(2016) [PDF]
Coverage Mechanism: "Modeling Coverage for Neural Machine Translation". ACL(2016) [PDF]
GAN: "Generative Adversarial Nets". NeurIPS(2014) [PDF]
SeqGAN: "SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient". AAAI(2017) [PDF] [code]
Multi-task Learning: "An Overview of Multi-Task Learning in Deep Neural Networks". arXiv(2017) [PDF]
Gradient Descent: "An Overview of Gradient Descent Optimization Algorithms". arXiv(2016) [PDF] ⭐️⭐️⭐️⭐️⭐️

Pre-trained Language Models

BART: "BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension". ACL(2020) [PDF] [code]
PLMs: "Pre-trained Models for Natural Language Processing: A Survey". arXiv(2020) [PDF]
ERNIE-GEN: "ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation". IJCAI(2020) [PDF] [code]
ALBERT: "ALBERT: A Lite BERT for Self-supervised Learning of Language Representations". ICLR(2020) [PDF]
TinyBERT: "TinyBERT: Distilling BERT for Natural Language Understanding". arXiv(2019) [PDF] [code]
Chinese BERT: "Pre-Training with Whole Word Masking for Chinese BERT". arXiv(2019) [PDF] [code]
SpanBERT: "SpanBERT: Improving Pre-training by Representing and Predicting Spans". TACL(2020) [PDF] [code]
RoBERTa: "RoBERTa: A Robustly Optimized BERT Pretraining Approach". arXiv(2019) [PDF] [code]
ERNIE(Tsinghua): "ERNIE: Enhanced Language Representation with Informative Entities". ACL(2019) [PDF] [code]
ERNIE(Baidu): "ERNIE: Enhanced Representation through Knowledge Integration". arXiv(2019) [PDF] [code]
UniLM: "Unified Language Model Pre-training for Natural Language Understanding and Generation". NeurIPS(2019) [PDF] [code] ⭐️⭐️⭐️⭐️⭐️
XLNet: "XLNet: Generalized Autoregressive Pretraining for Language Understanding". NeurIPS(2019) [PDF] [code]
XLM: "Cross-lingual Language Model Pretraining". NeurIPS(2019) [PDF] [code]
BERT: "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding". NAACL(2019) [PDF] [code] ⭐️⭐️⭐️⭐️⭐️

Dialogue System

PLMs for Dialogue

DialogBERT: "DialogBERT: Discourse-Aware Response Generation via Learning to Recover and Rank Utterances". AAAI(2021) [PDF]
CDial-GPT: "A Large-Scale Chinese Short-Text Conversation Dataset". NLPCC(2020) [PDF] [code]
ToD-BERT: "ToD-BERT: Pre-trained Natural Language Understanding for Task-Oriented Dialogues". arXiv(2020) [PDF] [code]
DialoGPT: "DialoGPT : Large-Scale Generative Pre-training for Conversational Response Generation". ACL(2020) [PDF] [code]
PLATO: "PLATO: Pre-trained Dialogue Generation Model with Discrete Latent Variable". ACL(2020) [PDF] [code]
Guyu: "An Empirical Investigation of Pre-Trained Transformer Language Models for Open-Domain Dialogue Generation". arXiv(2020) [PDF] [code]

Rec-oriented Dialogue (CRS)

CRS-Survey: "Advances and Challenges in Conversational Recommender Systems: A Survey ". arXiv(2021) [PDF]
CRS-Lab: "CRSLab: An Open-Source Toolkit for Building Conversational Recommender System". arXiv(2021) [PDF] [code] ⭐️⭐️⭐️
CR-Walker: "Bridging the Gap between Conversational Reasoning and Interactive Recommendation". arXiv(2020) [PDF] [code]
INSPIRED: "INSPIRED: Toward Sociable Recommendation Dialog Systems". EMNLP(2020) [PDF] [data]
TG-ReDial: "Towards Topic-Guided Conversational Recommender System". COLING(2020) [PDF] [code]
DuRecDial: "Towards Conversational Recommendation over Multi-Type Dialogs". ACL(2020) [PDF] [code] ⭐️⭐️⭐️
KGSF: "Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion". KDD(2020) [PDF] [code]
KBRD: "Towards Knowledge-Based Recommender Dialog System". EMNLP(2019) [PDF] [code]
GoRecDial: "Recommendation as a Communication Game: Self-Supervised Bot-Play for Goal-oriented Dialogue". EMNLP(2019) [PDF] [code]
ReDial: "Towards Deep Conversational Recommendations". NeurIPS(2018) [PDF] [data]

Knowledge-grounded Dialogue

DiffKS: "Difference-aware Knowledge Selection for Knowledge-grounded Conversation Generation". EMNLP-Findings(2020) [PDF] [code]
DukeNet: "DukeNet: A Dual Knowledge Interaction Network for Knowledge-Grounded Conversation". SIGIR(2020) [PDF] [code]
CCN: "Cross Copy Network for Dialogue Generation". EMNLP(2020) [PDF] [code]
PIPM: "Bridging the Gap between Prior and Posterior Knowledge Selection for Knowledge-Grounded Dialogue Generation". EMNLP(2020) [PDF]
ConKADI: "Diverse and Informative Dialogue Generation with Context-Specific Commonsense Knowledge Awareness". ACL(2020) [PDF] [code] ⭐️⭐️⭐️⭐️⭐️
KIC: "Generating Informative Conversational Response using Recurrent Knowledge-Interaction and Knowledge-Copy". ACL(2020) [PDF]
SKT: "Sequential Latent Knowledge Selection for Knowledge-Grounded Dialogue". ICLR(2020) [PDF] [code] ⭐️⭐️⭐️⭐️
KdConv: "KdConv: A Chinese Multi-domain Dialogue Dataset Towards Multi-turn Knowledge-driven Conversation". ACL(2020) [PDF] [data]
RefNet: "RefNet: A Reference-aware Network for Background Based Conversation". AAAI(2020) [PDF] [code]
GLKS: "Thinking Globally, Acting Locally: Distantly Supervised Global-to-Local Knowledge Selection for Background Based Conversation". AAAI(2020) [PDF] [code]
DuConv: "Proactive Human-Machine Conversation with Explicit Conversation Goals". ACL(2019) [PDF] [code]
PostKS: "Learning to Select Knowledge for Response Generation in Dialog Systems". IJCAI(2019) [PDF]
Two-Stage-Transformer: "Wizard of Wikipedia: Knowledge-Powered Conversational agents". ICLR(2019) [PDF]
NKD: "Knowledge Diffusion for Neural Dialogue Generation". ACL(2018) [PDF] [data]
Dual Fusion: "Smarter Response with Proactive Suggestion: A New Generative Neural Conversation Paradigm". IJCAI(2018) [PDF]
CCM: "Commonsense Knowledge Aware Conversation Generation with Graph Attention". IJCAI(2018) [PDF] [code] ⭐️⭐️⭐️⭐️⭐️
MTask: "A Knowledge-Grounded Neural Conversation Model". AAAI(2018) [PDF]
GenDS: "Flexible End-to-End Dialogue System for Knowledge Grounded Conversation". arXiv(2017) [PDF]

Task-oriented Dialogue

DDMN: "Dual Dynamic Memory Network for End-to-End Multi-turn Task-oriented Dialog Systems". COLING(2020) [PDF] [code] ⭐️⭐️⭐️
GraphDialog: "GraphDialog: Integrating Graph Knowledge into End-to-End Task-Oriented Dialogue Systems". EMNLP(2020) [PDF] [code]
DF-Net: "Dynamic Fusion Network for Multi-Domain End-to-end Task-Oriented Dialog". ACL(2020) [PDF] [code]
MALA: "MALA: Cross-Domain Dialogue Generation with Action Learning". AAAI(2020) [PDF]
Neural Task-Oriented Dialogue: "Learning to Memorize in Neural Task-Oriented Dialogue Systems". MPhil Thesis(2019) [PDF] ⭐️⭐️⭐️⭐️
GLMP: "Global-to-local Memory Pointer Networks for Task-Oriented Dialogue". ICLR(2019) [PDF] [code] ⭐️⭐️⭐️⭐️⭐️
KB Retriever: "Entity-Consistent End-to-end Task-Oriented Dialogue System with KB Retriever". EMNLP(2019) [PDF] [data]
TRADE: "Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems". ACL(2019) [PDF] [code]
WMM2Seq: "A Working Memory Model for Task-oriented Dialog Response Generation". ACL(2019) [PDF]
Pretrain-Fine-tune: "Training Neural Response Selection for Task-Oriented Dialogue Systems". ACL(2019) [PDF] [data]
Multi-level Mem: "Multi-Level Memory for Task Oriented Dialogs". NAACL(2019) [PDF] [code] ⭐️⭐️⭐️
BossNet: "Disentangling Language and Knowledge in Task-Oriented Dialogs ". NAACL(2019) [PDF] [code]
SL+RL: "Dialogue Learning with Human Teaching and Feedback in End-to-End Trainable Task-Oriented Dialogue Systems". NAACL(2018) [PDF]
MAD: "Memory-augmented Dialogue Management for Task-oriented Dialogue Systems". TOIS(2018) [PDF] ⭐️⭐️⭐️
TSCP: "Sequicity: Simplifying Task-oriented Dialogue Systems with Single Sequence-to-Sequence Architectures". ACL(2018) [PDF] [code]
Mem2Seq: "Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems". ACL(2018) [PDF] [code] ⭐️⭐️⭐️⭐️
Topic-Seg-Label: "A Weakly Supervised Method for Topic Segmentation and Labeling in Goal-oriented Dialogues via Reinforcement Learning". IJCAI(2018) [PDF] [code]
AliMe: "AliMe Chat: A Sequence to Sequence and Rerank based Chatbot Engine". ACL(2017) [PDF]
KVR Net: "Key-Value Retrieval Networks for Task-Oriented Dialogue". SIGDIAL(2017) [PDF] [data]

Open-domain Dialogue

CL4Dialogue: "Group-wise Contrastive Learning for Neural Dialogue Generation". EMNLP-Findings(2020) [PDF] [code] ⭐️⭐️⭐️
Neg-train: "Negative Training for Neural Dialogue Response Generation". ACL(2020) [PDF] [code]
HDSA: "Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attention". ACL(2019) [PDF] [code] ⭐️⭐️⭐️
CAS: "Skeleton-to-Response: Dialogue Generation Guided by Retrieval Memory". NAACL(2019) [PDF] [code]
Edit-N-Rerank: "Response Generation by Context-aware Prototype Editing". AAAI(2019) [PDF] [code] ⭐️⭐️⭐️
HVMN: "Hierarchical Variational Memory Network for Dialogue Generation". WWW(2018) [PDF] [code]
XiaoIce: "The Design and Implementation of XiaoIce, an Empathetic Social Chatbot". arXiv(2018) [PDF]
D2A: "Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base". NeurIPS(2018) [PDF] [code]
DAIM: "Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization". NeurIPS(2018) [PDF]
REASON: "Dialog Generation Using Multi-turn Reasoning Neural Networks". NAACL(2018) [PDF]
STD/HTD: "Learning to Ask Questions in Open-domain Conversational Systems with Typed Decoders". ACL(2018) [PDF] [code]
CSF: "Generating Informative Responses with Controlled Sentence Function". ACL(2018) [PDF] [code]
DAWnet: "Chat More: Deepening and Widening the Chatting Topic via A Deep Model". SIGIR(2018) [PDF] [code]
ZSDG: "Zero-Shot Dialog Generation with Cross-Domain Latent Actions". SIGDIAL(2018) [PDF] [code]
DUA: "Modeling Multi-turn Conversation with Deep Utterance Aggregation". COLING(2018) [PDF] [code]
Data-Aug: "Sequence-to-Sequence Data Augmentation for Dialogue Language Understanding". COLING(2018) [PDF] [code]
DC-MMI: "Generating More Interesting Responses in Neural Conversation Models with Distributional Constraints". EMNLP(2018) [PDF] [code]
cVAE-XGate/CGate: "Better Conversations by Modeling, Filtering, and Optimizing for Coherence and Diversity". EMNLP(2018) [PDF] [code]
Retrieval+multi-seq2seq: "An Ensemble of Retrieval-Based and Generation-Based Human-Computer Conversation Systems". IJCAI(2018) [PDF]
DAM: "Multi-Turn Response Selection for Chatbots with Deep Attention Matching Network". ACL(2018) [PDF] [code] ⭐️⭐️⭐️⭐️
SMN: "Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-Based Chatbots". ACL(2017) [PDF] [code] ⭐️⭐️⭐️
CVAE/KgCVAE: "Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders". ACL(2017) [PDF] [code] ⭐️⭐️⭐️
TA-Seq2Seq: "Topic Aware Neural Response Generation". AAAI(2017) [PDF] [code]
MA: "Mechanism-Aware Neural Machine for Dialogue Response Generation". AAAI(2017) [PDF]
VHRED: "A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues". AAAI(2017) [PDF] [code]
HRED: "Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models". AAAI(2016) [PDF] [code]
RL-Dialogue: "Deep Reinforcement Learning for Dialogue Generation". EMNLP(2016) [PDF]
MMI: "A Diversity-Promoting Objective Function for Neural Conversation Models". NAACL-HLT(2016) [PDF] [code]

Personalized Dialogue

PAML: "Personalizing Dialogue Agents via Meta-Learning". ACL(2019) [PDF] [code]
PCCM: "Assigning Personality/Profile to a Chatting Machine for Coherent Conversation Generation". IJCAI(2018) [PDF] [code]
ECM: "Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memory". AAAI(2018) [PDF] [code]

Miscellaneous

CrossWOZ: "CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset". TACL(2020) [PDF] [code]
MultiWOZ: "MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling". EMNLP(2018) [PDF] [code]
Survey of Dialogue: "A Survey on Dialogue Systems: Recent Advances and New Frontiers". SIGKDD Explorations(2017) [PDF]
Survey of Dialogue Corpora: "A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version". Dialogue & Discourse(2018) [PDF]
ADVMT: "One "Ruler" for All Languages: Multi-Lingual Dialogue Evaluation with Adversarial Multi-Task Learning". IJCAI(2018) [PDF]

Text Generation

Repetition-Problem-NLG: "A Theoretical Analysis of the Repetition Problem in Text Generation". AAAI(2021) [PDF] [code]
BERTSeq2Seq: "Leveraging Pre-trained Checkpoints for Sequence Generation Tasks". TACL(2020) [PDF] [code] ⭐️⭐️⭐️
CoMMA: "A Study of Non-autoregressive Model for Sequence Generation". ACL(2020) [PDF]
Nucleus Sampling: "The Curious Case of Neural Text Degeneration". ICLR(2020) [PDF] [code] ⭐️⭐️⭐️
Cascaded Generation: "Cascaded Text Generation with Markov Transformers". NeurIPS(2020) [PDF] [code]
Sequence Generation: "A Generalized Framework of Sequence Generation with Application to Undirected Sequence Models". arXiv(2019) [PDF] [code]
Sparse-Seq2Seq: "Sparse Sequence-to-Sequence Models". ACL(2019) [PDF] [code]

Knowledge Representation Learning

KEPLER: "KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation". TACL(2020) [PDF] [code]
GNTP: "Differentiable Reasoning on Large Knowledge Bases and Natural Language". AAAI(2020) [PDF] [code]
NTP: "End-to-End Differentiable Proving". NeurIPS(2017) [PDF] [code]

Text Summarization

BERTSum: "Fine-tune BERT for Extractive Summarization". arXiv(2019) [PDF] [code]
QASumm: "Guiding Extractive Summarization with Question-Answering Rewards". NAACL(2019) [PDF] [code]
Re^3Sum: "Retrieve, Rerank and Rewrite: Soft Template Based Neural Summarization". ACL(2018) [PDF] [code]
NeuSum: "Neural Document Summarization by Jointly Learning to Score and Select Sentences". ACL(2018) [PDF]
rnn-ext+abs+RL+rerank: "Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting". ACL(2018) [PDF] [Notes] [code] ⭐️⭐️⭐️⭐️⭐️
Seq2Seq+CGU: "Global Encoding for Abstractive Summarization". ACL(2018) [PDF] [code]
ML+RL: "A Deep Reinforced Model for Abstractive Summarization". ICLR(2018) [PDF]
T-ConvS2S: "Don’t Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization". EMNLP(2018) [PDF] [code]
RL-Topic-ConvS2S: "A reinforced topic-aware convolutional sequence-to-sequence model for abstractive text summarization". IJCAI (2018) [PDF]
GANsum: "Generative Adversarial Network for Abstractive Text Summarization". AAAI(2018) [PDF]
FTSum: "Faithful to the Original: Fact Aware Neural Abstractive Summarization". AAAI(2018) [PDF]
PGN: "Get To The Point: Summarization with Pointer-Generator Networks". ACL(2017) [PDF] [code] ⭐️⭐️⭐️⭐️⭐️
ABS/ABS+: "A Neural Attention Model for Abstractive Sentence Summarization". EMNLP(2015) [PDF]
RAS-Elman/RAS-LSTM: "Abstractive Sentence Summarization with Attentive Recurrent Neural Networks". NAACL(2016) [PDF] [code]

Topic Modeling

LDA: "Latent Dirichlet Allocation". JMLR(2003) [PDF] [code] ⭐️⭐️⭐️⭐️⭐️
Parameter Estimation: "Parameter estimation for text analysis". Technical report (2005). [PDF] ⭐️⭐️⭐️
DTM: "Dynamic Topic Models". ICML(2006) [PDF] [code] ⭐️⭐️⭐️⭐️
cDTM: "Continuous Time Dynamic Topic Models". UAI(2008) [PDF]
iDocNADE: "Document Informed Neural Autoregressive Topic Models with Distributional Prior". AAAI(2019) [PDF] [code]
NTM: "A Novel Neural Topic Model and Its Supervised Extension". AAAI(2015) [PDF]
TWE: "Topical Word Embeddings". AAAI(2015) [PDF]
RATM-D: "Recurrent Attentional Topic Model". AAAI(2017)[PDF]
RIBS-TM: "Don't Forget the Quantifiable Relationship between Words: Using Recurrent Neural Network for Short Text Topic Discovery". AAAI(2017) [PDF]
Topic coherence: "Optimizing Semantic Coherence in Topic Models". EMNLP(2011) [PDF]
Topic coherence: "Automatic Evaluation of Topic Coherence". NAACL(2010) [PDF]
DADT: "Authorship Attribution with Author-aware Topic Models". ACL(2012) [PDF]
Gaussian-LDA: "Gaussian LDA for Topic Models with Word Embeddings". ACL(2015) [PDF] [code] ⭐️⭐️⭐️
LFTM: "Improving Topic Models with Latent Feature Word Representations". TACL(2015) [PDF] [code]
TopicVec: "Generative Topic Embedding: a Continuous Representation of Documents". ACL(2016) [PDF] [code]
TopicRNN: "TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency". ICLR(2017) [PDF] [code] ⭐️⭐️⭐️⭐️⭐️
NMF boosted: "Stability of topic modeling via matrix factorization". Expert Syst. Appl. (2018) [PDF]
Topic2Vec: "Topic2Vec: Learning distributed representations of topics". IALP(2015) [PDF]
L-EnsNMF: "L-EnsNMF: Boosted Local Topic Discovery via Ensemble of Nonnegative Matrix Factorization". ICDM(2016) [PDF] [code] ⭐️⭐️⭐️⭐️
DC-NMF: "DC-NMF: nonnegative matrix factorization based on divide-and-conquer for fast clustering and topic modeling". J. Global Optimization (2017) [PDF]
cFTM: "The contextual focused topic model". KDD(2012) [PDF]
CLM: "Collaboratively Improving Topic Discovery and Word Embeddings by Coordinating Global and Local Contexts". KDD(2017) [PDF] [code] ⭐️⭐️⭐️⭐️⭐️
GMTM: "Unsupervised Topic Modeling for Short Texts Using Distributed Representations of Words". NAACL(2015) [PDF]
GPU-PDMM: "Enhancing Topic Modeling for Short Texts with Auxiliary Word Embeddings". TOIS (2017) [PDF]
BPT: "A Two-Level Topic Model Towards Knowledge Discovery from Citation Networks". TKDE (2014) [PDF]
BTM: "A Biterm Topic Model for Short Texts". WWW(2013) [PDF] [code] ⭐️⭐️⭐️⭐️
HGTM: "Using Hashtag Graph-Based Topic Model to Connect Semantically-Related Words Without Co-Occurrence in Microblogs". TKDE(2016) [PDF]

Machine Translation

Multi-pass decoder: "Adaptive Multi-pass Decoder for Neural Machine Translation". EMNLP(2018) [PDF]
Deliberation Networks: "Deliberation Networks: Sequence Generation Beyond One-Pass Decoding". NeurIPS(2017) [PDF] ⭐️⭐️⭐️
KVMem-Attention: "Neural Machine Translation with Key-Value Memory-Augmented Attention". IJCAI(2018) [PDF] ⭐️⭐️⭐️
Interactive-Attention: "Interactive Attention for Neural Machine Translation". COLING(2016) [PDF]

Question Answering

CFC: "Coarse-grain Fine-grain Coattention Network for Multi-evidence Question Answering". ICLR(2019) [PDF]
MTQA: "Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question Answering". AAAI(2019) [PDF] [code]
CQG-KBQA: "Knowledge Base Question Answering via Encoding of Complex Query Graphs". EMNLP(2018) [PDF] [code] ⭐️⭐️⭐️⭐️⭐️
HR-BiLSTM: "Improved Neural Relation Detection for Knowledge Base Question Answering". ACL(2017) [PDF]
KBQA-CGK: "An End-to-End Model for Question Answering over Knowledge Base with Cross-Attention Combining Global Knowledge". ACL(2017) [PDF]
KVMem: "Key-Value Memory Networks for Directly Reading Documents". EMNLP(2016) [PDF]

Reading Comprehension

DecompRC: "Multi-hop Reading Comprehension through Question Decomposition and Rescoring". ACL(2019) [PDF] [code]
FlowQA: "FlowQA: Grasping Flow in History for Conversational Machine Comprehension". ICLR(2019) [PDF] [code] ⭐️⭐️⭐️⭐️
SDNet: "SDNet: Contextualized Attention-based Deep Network for Conversational Question Answering". arXiv(2018) [PDF] [code]
MacNet: "MacNet: Transferring Knowledge from Machine Comprehension to Sequence-to-Sequence Models". NeurIPS(2018) [PDF]

Image Captioning

MLAIC: "A Multi-task Learning Approach for Image Captioning". IJCAI(2018) [PDF] [code]
Up-Down Attention: "Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering". CVPR(2018) [PDF] ⭐️⭐️⭐️
SCST: "Self-critical Sequence Training for Image Captioning". CVPR(2017) [PDF] ⭐️⭐️⭐️

Text Matching

Poly-encoder: "Poly-encoders: Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scorings". ICLR(2020) [PDF] [code]
AugSBERT: "Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks". arXiv(2020) [PDF] [code]
SBERT: "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks". EMNLP(2019) [PDF] [code]

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].

Stars: ✭ 508

Visit Git Page 🔗Visit User Page 🔗Visit Issues Page (0) 🔗