简版-翻译、摘要、会话、文本生成任务顶会论文

机器翻译

ACL

序号	会议/期刊	论文	主要技术	代码	论文下载地址
1	ACL2019	Latent Variable Model for Multi-modal Translation		https://github.com/iacercalixto/variational_mmt	https://arxiv.org/pdf/1811.00357
2	ACL2021	Rewriter-Evaluator Architecture for Neural Machine Translation			https://arxiv.org/pdf/2012.05414
3	ACL2021	Consistency Regularization for Cross-Lingual Fine-Tuning		https://github.com/bozheng-hit/xTune	https://arxiv.org/pdf/2106.08226
4	ACL2021	Improving Pretrained Cross-Lingual Language Models via Self-Labeled Word Alignment		https://github.com/CZWin32768/XLM-Align	https://arxiv.org/pdf/2106.06381
5	ACL2021	Improving Zero-Shot Translation by Disentangling Positional Information		https://github.com/nlp-dke/NMTGMinor/tree/master/recipes/zero-shot	https://arxiv.org/pdf/2012.15127
6	ACL2021	Beyond Offline Mapping: Learning Cross-lingual Word Embeddings through Context Anchoring			https://arxiv.org/pdf/2012.15715
7	ACL2021	Verb Knowledge Injection for Multilingual Event Processing			https://arxiv.org/pdf/2012.15421
8	ACL2021	Common Sense Beyond English: Evaluating and Improving Multilingual Language Models for Commonsense Reasoning		https://github.com/INK-USC/XCSR	https://arxiv.org/pdf/2106.06937
9	ACL2021	Bilingual Lexicon Induction via Unsupervised Bitext Construction and Word Alignment			https://arxiv.org/pdf/2101.00148
10	ACL2020	Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation		https://github.com/bzhangGo/zero	https://arxiv.org/pdf/2004.11867
11	ACL2020	Simultaneous Translation Policies: From Fixed to Adaptive			https://arxiv.org/pdf/2004.13169
12	ACL2020	Multiscale Collaborative Deep Models for Neural Machine Translation		https://github.com/pemywei/MSC-NMT	https://arxiv.org/pdf/2004.14021
13	ACL2020	Character-Level Translation with Self-attention			https://arxiv.org/pdf/2004.14788
14	ACL2020	ENGINE: Energy-Based Inference Networks for Non-Autoregressive Machine Translation		https://github.com/lifu-tu/ENGINE	https://arxiv.org/pdf/2005.00850
15	ACL2020	Selecting Backtranslated Data from Multiple Sources for Improved Neural Machine Translation			https://arxiv.org/pdf/2005.00308
16	ACL2020	Dynamic Programming Encoding for Subword Segmentation in Neural Machine Translation		https://github.com/xlhex/dpe	https://arxiv.org/pdf/2005.06606
17	ACL2020	Norm-Based Curriculum Learning for Neural Machine Translation		https://github.com/NLP2CT/norm-nmt	https://arxiv.org/pdf/2006.02014
18	ACL2020	Bilingual Dictionary Based Neural Machine Translation without Using Parallel Sentences		https://github.com/mttravel/Dictionary-based-MT	https://arxiv.org/pdf/2007.02671
19	ACL2020	Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation		https://github.com/bzhangGo/zero	https://arxiv.org/pdf/2004.11867
20	ACL2020	ENGINE: Energy-Based Inference Networks for Non-Autoregressive Machine Translation		https://github.com/lifu-tu/ENGINE	https://arxiv.org/pdf/2005.00850
21	ACL2019	An Effective Approach to Unsupervised Machine Translation		https://github.com/artetxem/monoses	https://arxiv.org/pdf/1902.01313
22	ACL2019	When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion		https://github.com/lena-voita/good-translation-wrong-in-context	https://arxiv.org/pdf/1905.05979
23	ACL2019	Syntactically Supervised Transformers for Faster Neural Machine Translation		https://github.com/dojoteef/synst	https://arxiv.org/pdf/1906.02780
24	ACL2019	Evaluating Gender Bias in Machine Translation			https://arxiv.org/pdf/2106.08680
25	ACL2019	Learning Deep Transformer Models for Machine Translation		https://github.com/wangqiangneu/dlcl	https://arxiv.org/pdf/1906.01787
26	ACL2019	Domain Adaptation of Neural Machine Translation by Lexicon Induction			https://arxiv.org/pdf/1906.00376
27	ACL2019	Retrieving Sequential Information for Non-Autoregressive Neural Machine Translation		https://github.com/ictnlp/RSI-NAT	https://arxiv.org/pdf/1906.09444
28	ACL2019	Robust Neural Machine Translation with Joint Textual and Phonetic Embedding			https://arxiv.org/pdf/1810.06729
29	ACL2019	Simple and Effective Paraphrastic Similarity from Parallel Translations			https://arxiv.org/pdf/1909.13872
30	ACL2019	Unsupervised Question Answering by Cloze Translation		https://github.com/facebookresearch/UnsupervisedQA	https://arxiv.org/pdf/1906.04980
31	ACL2019	Bilingual Lexicon Induction through Unsupervised Machine Translation		https://github.com/artetxem/monoses	https://arxiv.org/pdf/1907.10761
32	ACL2019	Soft Contextual Data Augmentation for Neural Machine Translation		https://github.com/teslacool/SCA	https://arxiv.org/pdf/1905.10523
33	ACL2019	Generalized Data Augmentation for Low-Resource Translation			https://arxiv.org/pdf/1906.03785

EMNLP

序号	会议/期刊	论文	主要技术	代码	论文下载地址
1	EMNLP2020	Fully Quantized Transformer for Machine Translation			https://arxiv.org/pdf/1910.10485
2	EMNLP2020	Fixed Encoder Self-Attention Patterns in Transformer-Based Machine Translation			https://arxiv.org/pdf/2002.10260
3	EMNLP2020	Adversarial Subword Regularization for Robust Neural Machine Translation		https://github.com/dmis-lab/AdvSR	https://arxiv.org/pdf/2004.14109
4	EMNLP2020	Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages		https://github.com/masakhane-io/masakhane-mt	https://arxiv.org/pdf/2010.02353
5	EMNLP2020	On Romanization for Model Transfer Between Scripts in Neural Machine Translation			https://arxiv.org/pdf/2009.14824
6	EMNLP2020	Graph-to-Tree Neural Networks for Learning Structured Input-Output Translation with Applications to Semantic Parsing and Math Word Problem		https://github.com/IBM/Graph2Tree	https://arxiv.org/pdf/2004.13781
7	EMNLP2020	On Long-Tailed Phenomena in Neural Machine Translation		https://github.com/vyraun/long-tailed	https://arxiv.org/pdf/2010.04924
8	EMNLP2020	A Multilingual View of Unsupervised Machine Translation			https://arxiv.org/pdf/2002.02955
9	EMNLP2019	Explicit Cross-lingual Pre-training for Unsupervised Machine Translation			https://arxiv.org/pdf/1909.00180
10	EMNLP2019	Improving Back-Translation with Uncertainty-based Confidence Estimation		https://github.com/THUNLP-MT/UCE4BT	https://arxiv.org/pdf/1909.00157
11	EMNLP2019	Iterative Dual Domain Adaptation for Neural Machine Translation			https://arxiv.org/pdf/1912.07239
12	EMNLP2019	Context-Aware Monolingual Repair for Neural Machine Translation		https://github.com/lena-voita/good-translation-wrong-in-context	https://arxiv.org/pdf/1909.01383
13	EMNLP2019	Dynamic Past and Future for Neural Machine Translation		https://github.com/zhengzx-nlp/dynamic-nmt	https://arxiv.org/pdf/1904.09646
14	EMNLP2019	Simpler and Faster Learning of Adaptive Policies for Simultaneous Translation			https://arxiv.org/pdf/1909.01559
15	EMNLP2019	Unsupervised Domain Adaptation for Neural Machine Translation with Domain-Aware Feature Embeddings		https://github.com/zdou0830/DAFE	https://arxiv.org/pdf/1908.10430
16	EMNLP2019	Controlling Text Complexity in Neural Machine Translation		https://github.com/sweta20/ComplexityControlledMT	https://arxiv.org/pdf/1911.00835
17	EMNLP2019	Simple and Effective Noisy Channel Modeling for Neural Machine Translation		https://github.com/pytorch/fairseq	https://arxiv.org/pdf/1908.05731
18	EMNLP2019	Hint-Based Training for Non-Autoregressive Machine Translation		https://github.com/zhuohan123/hint-nart	https://arxiv.org/pdf/1909.06708

NAACL

序号	会议/期刊	论文	主要技术	代码	论文下载地址
1	NAACL2021	Self-Training for Unsupervised Neural Machine Translation in Unbalanced Training Data Scenarios			https://arxiv.org/pdf/2004.04507
2	NAACL2021	Harnessing Multilinguality in Unsupervised Machine Translation for Rare Languages			https://arxiv.org/pdf/2009.11201
3	NAACL2021	Towards Continual Learning for Multilingual Machine Translation via Vocabulary Substitution			https://arxiv.org/pdf/2103.06799
4	NAACL2021	Probing Word Translations in the Transformer and Trading Decoder for Encoder Layers			https://arxiv.org/pdf/2003.09586
5	NAACL2021	Sequence Tagging and Machine Translation			https://arxiv.org/pdf/1911.00234
6	NAACL2021	Neural Machine Translation without Embeddings		https://github.com/UriSha/EmbeddinglessNMT	https://arxiv.org/pdf/2008.09396
7	NAACL2021	From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding		https://bitbucket.org/robvanderg/xsid	https://arxiv.org/pdf/2105.07316
8	NAACL2021	Improving the Lexical Ability of Pretrained Language Models for Unsupervised Neural Machine Translation		https://github.com/alexandra-chron/lexical_xlm_relm	https://arxiv.org/pdf/2103.10531
9	NAACL2021	Multi-Task Learning with Shared Encoder for Non-Autoregressive Machine Translation		https://github.com/yongchanghao/multi-task-nat	https://arxiv.org/pdf/2010.12868
10	NAACL2021	Assessing Reference-Free Peer Evaluation for Machine Translation			https://arxiv.org/pdf/2104.05146
11	NAACL2021	Generative Imagination Elevates Machine Translation			https://arxiv.org/pdf/2009.09654
12	NAACL2021	Context-aware Decoder for Neural Machine Translation using a Target-side Document-Level Language Model			https://arxiv.org/pdf/2010.12827
13	NAACL2021	Restoring and Mining the Records of the Joseon Dynasty via Neural Language Modeling and Machine Translation			https://arxiv.org/pdf/2104.05964
14	NAACL2021	The Curious Case of Hallucinations in Neural Machine Translation		https://github.com/vyraun/hallucinations	https://arxiv.org/pdf/2104.06683
15	NAACL2021	Revisiting the Weaknesses of Reinforcement Learning for Neural Machine Translation		https://github.com/samuki/reinforce-joey	https://arxiv.org/pdf/2106.08942
16	NAACL2021	Cross-lingual Supervision Improves Unsupervised Neural Machine Translation			https://arxiv.org/pdf/2004.03137
17	NAACL2019	ReWE: Regressing Word Embeddings for Regularization of Neural Machine Translation Systems			https://arxiv.org/pdf/1904.02461
18	NAACL2019	Lost in Machine Translation: A Method to Reduce Meaning Loss		https://github.com/reubenharry/pragmatic-translation	https://arxiv.org/pdf/1902.09514
19	NAACL2019	Syntax-Enhanced Neural Machine Translation with Syntax-Aware Word Representations			https://arxiv.org/pdf/1905.02878
20	NAACL2019	Improving Robustness of Machine Translation with Synthetic Noise		https://github.com/MysteryVaibhav/robust_mtnt	https://arxiv.org/pdf/1902.09508
21	NAACL2019	Differentiable Sampling with Flexible Reference Word Order for Neural Machine Translation		https://github.com/Izecson/saml-nmt	https://arxiv.org/pdf/1904.04079
22	NAACL2019	Fluent Translations from Disfluent Speech in End-to-End Speech Translation			https://arxiv.org/pdf/1906.00556
23	NAACL2019	Selective Attention for Context-aware Neural Machine Translation		https://github.com/sameenmaruf/selective-attn	https://arxiv.org/pdf/1903.08788

COLING

序号	会议/期刊	论文	主要技术	代码	论文下载地址
1	COLING2020	Emergent Communication Pretraining for Few-Shot Machine Translation		https://github.com/cambridgeltl/ECNMT	https://arxiv.org/pdf/2011.00890
2	COLING2020	Investigating Catastrophic Forgetting During Continual Training for Neural Machine Translation			https://arxiv.org/pdf/2011.00678
3	COLING2020	Layer-wise Multi-view Learning for Neural Machine Translation			https://arxiv.org/pdf/2011.01482
4	COLING2020	Leveraging Discourse Rewards for Document-Level Neural Machine Translation			https://arxiv.org/pdf/2010.03732
5	COLING2020	Optimized Transformer for Low-resource Neural Machine Translation			https://arxiv.org/pdf/2011.02266
6	COLING2020	Robust Unsupervised Neural Machine Translation with Adversarial Denoising Training			https://arxiv.org/pdf/2002.12549
7	COLING2020	Token Drop mechanism for Neural Machine Translation		https://github.com/zhajiahe/Token_Drop	https://arxiv.org/pdf/2010.11018
8	COLING2020	Understanding Pure Character-Based Neural Machine Translation: The Case of Translating Finnish into English			https://arxiv.org/pdf/2011.03469

会话/对话系统

ACL

序号	会议/期刊	论文	主要技术	代码	论文下载地址
1	ACL2021	TicketTalk: Toward human-level performance with end-to-end, transaction-based dialog systems			https://arxiv.org/pdf/2012.12458
2	ACL2021	HERALD: An Annotation Efficient Method to Detect User Disengagement in Social Conversations		https://github.com/Weixin-Liang/HERALD	https://arxiv.org/pdf/2106.00162
3	ACL2021	Maria: A Visual Experience Powered Conversational Agent		https://github.com/jokieleung/Maria	https://arxiv.org/pdf/2105.13073
4	ACL2021	Dialogue Response Selection with Hierarchical Curriculum Learning			https://arxiv.org/pdf/2012.14756
5	ACL2021	Diversifying Dialog Generation via Adaptive Label Smoothing		https://github.com/lemon234071/AdaLabel	https://arxiv.org/pdf/2105.14556
6	ACL2021	BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data		https://github.com/songhaoyu/BoB	https://arxiv.org/pdf/2106.06169
7	ACL2021	I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling			https://arxiv.org/pdf/2012.13391
8	ACL2021	A Sequence-to-Sequence Approach to Dialogue State Tracking		https://github.com/sweetalyssum/Seq2Seq-DU	https://arxiv.org/pdf/2011.09553
9	ACL2021	Generating Relevant and Coherent Dialogue Responses using Self-Separated Conditional Variational AutoEncoders			https://arxiv.org/pdf/2106.03410
10	ACL2021	Intent Classification and Slot Filling for Privacy Policies		https://github.com/wasiahmad/PolicyIE	https://arxiv.org/pdf/2101.00123
11	ACL2021	Dual Slot Selector via Local Reliability Verification for Dialogue State Tracking		https://github.com/guojinyu88/DSSDST	https://arxiv.org/pdf/2107.12578
12	ACL2021	Learning from Perturbations: Diverse and Informative Dialogue Generation with Inverse Adversarial Training			https://arxiv.org/pdf/2105.15171
13	ACL2021	Modeling Bilingual Conversational Characteristics for Neural Chat Translation		https://github.com/XL2248/CPCC	https://arxiv.org/pdf/2107.11164
14	ACL2020	Dynamic Fusion Network for Multi-Domain End-to-end Task-Oriented Dialog		https://github.com/LooperXX/DF-Net	https://arxiv.org/pdf/2004.11019
15	ACL2020	Learning Dialog Policies from Weak Demonstrations			https://arxiv.org/pdf/2004.11054
16	ACL2020	Span-ConveRT: Few-shot Span Extraction for Dialog with Pretrained Conversational Representations		https://github.com/PolyAI-LDN/task-specific-datasets	https://arxiv.org/pdf/2005.08866
17	ACL2020	Diversifying Dialogue Generation with Non-Conversational Text		https://github.com/chin-gyou/Div-Non-Conv	https://arxiv.org/pdf/2005.04346
18	ACL2020	Grounding Conversations with Improvised Dialogues		https://github.com/wise-east/spolin	https://arxiv.org/pdf/2004.09544
19	ACL2020	Designing Precise and Robust Dialogue Response Evaluators		https://github.com/ZHAOTING/dialog-processing	https://arxiv.org/pdf/2004.04908
20	ACL2020	PLATO: Pre-trained Dialogue Generation Model with Discrete Latent Variable		https://github.com/PaddlePaddle/Research	https://arxiv.org/pdf/1910.07931
21	ACL2020	Zero-Shot Transfer Learning with Synthesized Data for Multi-Domain Dialogue State Tracking		https://github.com/stanford-oval/zero-shot-multiwoz-acl2020	https://arxiv.org/pdf/2005.00891
22	ACL2020	Multi-Agent Task-Oriented Dialog Policy Learning with Role-Aware Reward Decomposition		https://github.com/truthless11/MADPL	https://arxiv.org/pdf/2004.03809
23	ACL2020	Towards Conversational Recommendation over Multi-Type Dialogs		https://github.com/PaddlePaddle/models	https://arxiv.org/pdf/2005.03954
24	ACL2020	KdConv: A Chinese Multi-domain Dialogue Dataset Towards Multi-turn Knowledge-driven Conversation		https://github.com/thu-coai/KdConv	https://arxiv.org/pdf/2004.04100
25	ACL2019	Incremental Transformer with Deliberation Decoder for Document Grounded Conversations		https://github.com/lizekang/ITDD	https://arxiv.org/pdf/1907.08854
26	ACL2019	E3: Entailment-driven Extracting and Editing for Conversational Machine Reading		https://github.com/vzhong/e3	https://arxiv.org/pdf/1906.05373
27	ACL2019	Improving Multi-turn Dialogue Modelling with Utterance ReWriter			https://arxiv.org/pdf/1906.07004
28	ACL2019	Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attention		https://github.com/wenhuchen/HDSA-Dialog	https://arxiv.org/pdf/1905.12866
29	ACL2019	Observing Dialogue in Therapy: Categorizing and Forecasting Behavioral Codes		https://github.com/utahnlp/therapist-observer	https://arxiv.org/pdf/1907.00326
30	ACL2019	Multimodal Transformer Networks for End-to-End Video-Grounded Dialogue Systems		https://github.com/henryhungle/MTN	https://arxiv.org/pdf/1907.01166
31	ACL2019	Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good		https://gitlab.com/ucdavisnlp/persuasionforgood	https://arxiv.org/pdf/1906.06725

EMNLP

序号	会议/期刊	论文	主要技术	代码	论文下载地址
1	EMNLP2020	Difference-aware Knowledge Selection for Knowledge-grounded Conversation Generation		https://github.com/chujiezheng/DiffKS	https://arxiv.org/pdf/2009.09378
2	EMNLP2020	Few-shot Natural Language Generation for Task-Oriented Dialog		https://github.com/pengbaolin/SC-GPT	https://arxiv.org/pdf/2002.12328
3	EMNLP2020	Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems		https://github.com/HLTCHKUST/ke-dialogue	https://arxiv.org/pdf/2009.13656
4	EMNLP2020	Plug-and-Play Conversational Models		https://github.com/andreamad8/PPCM	https://arxiv.org/pdf/2010.04344
5	EMNLP2020	COSMIC: COmmonSense knowledge for eMotion Identification in Conversations		https://github.com/declare-lab/conv-emotion	https://arxiv.org/pdf/2010.02795
6	EMNLP2020	Generalizable and Explainable Dialogue Generation via Explicit Action Learning			https://arxiv.org/pdf/2010.03755
7	EMNLP2020	Effects of Naturalistic Variation in Goal-Oriented Dialog		https://github.com/IBM/naturalistic-variation-goal-oriented-dialog-datasets	https://arxiv.org/pdf/2010.02260
8	EMNLP2019	DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation		https://github.com/SenticNet/conv-emotion	https://arxiv.org/pdf/1908.11540
9	EMNLP2019	Modeling Multi-Action Policy for Task-Oriented Dialogues			https://arxiv.org/pdf/1908.11546
10	EMNLP2019	Automatically Learning Data Augmentation Policies for Dialogue Tasks		https://github.com/WolfNiu/AutoAugDialogue	https://arxiv.org/pdf/1909.12868
11	EMNLP2019	Dependency Parsing for Spoken Dialog Systems			https://arxiv.org/pdf/1909.03317
12	EMNLP2019	Towards Knowledge-Based Recommender Dialog System		https://github.com/THUDM/KBRD	https://arxiv.org/pdf/1908.05391
13	EMNLP2019	DyKgChat: Benchmarking Dialogue Generation Grounding on Dynamic Knowledge Graphs		https://github.com/Pascalson/DyKGChat	https://arxiv.org/pdf/1910.00610
14	EMNLP2019	How to Build User Simulators to Train RL-based Dialog Systems		https://github.com/wyshi/user-simulator	https://arxiv.org/pdf/1909.01388
15	EMNLP2019	Dual Attention Networks for Visual Reference Resolution in Visual Dialog		https://github.com/gicheonkang/DAN-VisDial	https://arxiv.org/pdf/1902.09368
16	EMNLP2019	Dialog Intent Induction with Deep Multi-View Clustering		https://github.com/asappresearch/dialog-intent-induction	https://arxiv.org/pdf/1908.11487
17	EMNLP2019	Multi-Task Learning for Conversational Question Answering over a Large-Scale Knowledge Base		https://github.com/taoshen58/MaSP	https://arxiv.org/pdf/1910.05069

NAACL

序号	会议/期刊	论文	主要技术	代码	论文下载地址
1	NAACL2021	Open-Domain Question Answering Goes Conversational via Question Rewriting		https://github.com/apple/ml-qrecc	https://arxiv.org/pdf/2010.04898
2	NAACL2021	Action-Based Conversations Dataset: A Corpus for Building More In-Depth Task- Oriented Dialogue Systems		https://github.com/asappresearch/abcd	https://arxiv.org/pdf/2104.00783
3	NAACL2021	Self-Supervised Contrastive Learning for Efficient User Satisfaction Prediction in Conversational Agents			https://arxiv.org/pdf/2010.11230
4	NAACL2021	Human-like informative conversations: Better acknowledgements using conditional mutual information		https://github.com/AshwinParanjape/human-like-informative-conversations	https://arxiv.org/pdf/2104.07831
5	NAACL2021	DiSCoL: Toward Engaging Dialogue Systems through Conversational Line Guided Response Generation			https://arxiv.org/pdf/2102.02191
6	NAACL2021	Adding Chit-Chat to Enhance Task-Oriented Dialogues			https://arxiv.org/pdf/2010.12757
7	NAACL2021	Fast and Scalable Dialogue State Tracking with Explicit Modular Decomposition			https://arxiv.org/pdf/2004.10663
8	NAACL2019	Cross-lingual Transfer Learning for Multilingual Task Oriented Dialog			https://arxiv.org/pdf/1810.13327
9	NAACL2019	Evaluating Coherence in Dialogue Systems using Entailment		https://github.com/nouhadziri/DialogEntailment	https://arxiv.org/pdf/1904.03371

COLING

序号	会议/期刊	论文	主要技术	代码	论文下载地址
1	COLING2020	A Taxonomy of Empathetic Response Intents in Human Social Conversations		https://github.com/anuradha1992/EmpatheticIntents	https://arxiv.org/pdf/2012.04080
2	COLING2020	CEREC: A Corpus for Entity Resolution in Email Conversations		https://github.com/paragdakle/emailcoref	https://arxiv.org/pdf/2105.10606
3	COLING2020	Conversational Machine Comprehension: a Literature Review			https://arxiv.org/pdf/2006.00671
4	COLING2020	Improving Conversational Question Answering Systems after Deployment using Feedback-Weighted Learning		https://github.com/jjacampos/FeedbackWeightedLearning	https://arxiv.org/pdf/2011.00615
5	COLING2020	Towards Topic-Guided Conversational Recommender System		https://github.com/RUCAIBox/TG-ReDial	https://arxiv.org/pdf/2010.04125
6	COLING2020	Deconstruct to Reconstruct a Configurable Evaluation Metric for Open-Domain Dialogue Systems		https://github.com/vitouphy/usl_dialogue_metric	https://arxiv.org/pdf/2011.00483
7	COLING2020	Recent Neural Methods on Slot Filling and Intent Classification for Task-Oriented Dialogue Systems: A Survey			https://arxiv.org/pdf/2011.00564

文本生成

ACL

序号	会议/期刊	论文	主要技术	代码	论文下载地址
1	ACL2021	Generalising Multilingual Concept-to-Text NLG with Language Agnostic Delexicalisation			https://arxiv.org/pdf/2105.03432
2	ACL2021	Prefix-Tuning: Optimizing Continuous Prompts for Generation			https://arxiv.org/pdf/2101.00190
3	ACL2021	Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models		https://github.com/tongshuangwu/polyjuice	https://arxiv.org/pdf/2101.00288
4	ACL2021	Conditional Generation of Temporally-ordered Event Sequences			https://arxiv.org/pdf/2012.15786
5	ACL2021	Writing by Memorizing: Hierarchical Retrieval-based Medical Report Generation			https://arxiv.org/pdf/2106.06471
6	ACL2021	Factorising Meaning and Form for Intent-Preserving Paraphrasing		https://github.com/tomhosking/separator	https://arxiv.org/pdf/2105.15053
7	ACL2021	Improving Formality Style Transfer with Context-Aware Rule Injection			https://arxiv.org/pdf/2106.00210
8	ACL2021	DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling			https://arxiv.org/pdf/2107.01875
9	ACL2021	Generating Landmark Navigation Instructions from Maps as a Graph-to-Text Problem			https://arxiv.org/pdf/2012.15329
10	ACL2021	One2Set: Generating Diverse Keyphrases as a Set		https://github.com/jiacheng-ye/kg_one2set	https://arxiv.org/pdf/2105.11134
11	ACL2020	Distilling Knowledge Learned in BERT for Text Generation		https://github.com/ChenRocks/Distill-BERT-Textgen	https://arxiv.org/pdf/1911.03829
12	ACL2020	Rigid Formats Controlled Text Generation		https://github.com/lipiji/SongNet	https://arxiv.org/pdf/2004.08022
13	ACL2020	Semantic Graphs for Generating Deep Questions		https://github.com/WING-NUS/SG-Deep-Question-Generation	https://arxiv.org/pdf/2004.12704
14	ACL2020	Politeness Transfer: A Tag and Generate Approach			https://arxiv.org/pdf/2004.14257
15	ACL2020	GPT-too: A language-model-first approach for AMR-to-text generation		https://github.com/IBM/GPT-too-AMR2text	https://arxiv.org/pdf/2005.09123
16	ACL2020	Posterior Control of Blackbox Generation		https://github.com/XiangLi1999/PosteriorControl-NLG	https://arxiv.org/pdf/2005.04560
17	ACL2020	Parallel Data Augmentation for Formality Style Transfer		https://github.com/lancopku/Augmented_Data_for_FST	https://arxiv.org/pdf/2005.07522
18	ACL2020	Neural Data-to-Text Generation via Jointly Learning the Segmentation and Correspondence			https://arxiv.org/pdf/2005.01096
19	ACL2020	BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension			https://arxiv.org/pdf/1910.13461
20	ACL2020	Pre-train and Plug-in: Flexible Conditional Text Generation with Variational Auto- Encoders		https://github.com/WHUIR/PPVAE	https://arxiv.org/pdf/1911.03882
21	ACL2020	Two Birds, One Stone: A Simple, Unified Model for Text Generation from Structured and Unstructured Data		https://github.com/h-shahidi/2birds-gen	https://arxiv.org/pdf/1909.10158
22	ACL2020	Unsupervised Opinion Summarization as Copycat-Review Generation		https://github.com/ixlan/CopyCat-abstractive-opinion-summarizer	https://arxiv.org/pdf/1911.02247
23	ACL2020	Evidence-Aware Inferential Text Generation with Vector Quantised Variational AutoEncoder		https://github.com/microsoft/EA-VQ-VAE	https://arxiv.org/pdf/2006.08101
24	ACL2020	BLEURT: Learning Robust Metrics for Text Generation		https://github.com/google-research/bleurt	https://arxiv.org/pdf/2004.04696
25	ACL2019	Automatic Generation of High Quality CCGbanks for Parser Domain Adaptation			https://arxiv.org/pdf/1906.01834
26	ACL2019	PaperRobot: Incremental Draft Generation of Scientific Ideas		https://github.com/EagleW/PaperRobot	https://arxiv.org/pdf/1905.07870
27	ACL2019	Data-to-text Generation with Entity Modeling		https://github.com/ratishsp/data2text-entity-py	https://arxiv.org/pdf/1906.03221
28	ACL2019	Key Fact as Pivot: A Two-Stage Model for Low Resource Table-to-Text Generation		https://github.com/lancopku/Pivot	https://arxiv.org/pdf/1908.03067
29	ACL2019	Reinforced Dynamic Reasoning for Conversational Question Generation		https://github.com/ZJULearning/ReDR	https://arxiv.org/pdf/1907.12667
30	ACL2019	Neural Keyphrase Generation via Reinforcement Learning with Adaptive Rewards		https://github.com/kenchan0226/keyphrase-generation-rl	https://arxiv.org/pdf/1906.04106
31	ACL2019	Topic-Aware Neural Keyphrase Generation for Social Media Language		https://github.com/yuewang-cuhk/TAKG	https://arxiv.org/pdf/1906.03889
32	ACL2019	Argument Generation with Retrieval, Planning, and Realization			https://arxiv.org/pdf/1906.03717
33	ACL2019	Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attention		https://github.com/wenhuchen/HDSA-Dialog	https://arxiv.org/pdf/1905.12866
34	ACL2019	Coherent Comments Generation for Chinese Articles with a Graph-to-Sequence Model		https://github.com/lancopku/Graph-to-seq-comment-generation	https://arxiv.org/pdf/1906.01231
35	ACL2019	Cross-Lingual Training for Automatic Question Generation		https://github.com/vishwajeet93/clqg	https://arxiv.org/pdf/1906.02525
36	ACL2019	Graph Neural Networks with Generated Parameters for Relation Extraction			https://arxiv.org/pdf/1902.00756
37	ACL2019	Learning to Select, Track, and Generate for Data-to-Text		https://github.com/aistairc/rotowire-modified	https://arxiv.org/pdf/1907.09699
38	ACL2019	Predicting Human Activities from User-Generated Content			https://arxiv.org/pdf/1907.08540

EMNLP

序号	会议/期刊	论文	主要技术	代码	论文下载地址
1	EMNLP2020	Few-shot Natural Language Generation for Task-Oriented Dialog		https://github.com/pengbaolin/SC-GPT	https://arxiv.org/pdf/2002.12328
2	EMNLP2020	How Decoding Strategies Affect the Verifiability of Generated Text			https://arxiv.org/pdf/1911.03587
3	EMNLP2020	Control, Generate, Augment: A Scalable Framework for Multi-Attribute Text Generation			https://arxiv.org/pdf/2004.14983
4	EMNLP2020	Pretrained Language Models for Dialogue Generation with Multiple Input Sources		https://github.com/caoyu-noob/Multi-GPT2	https://arxiv.org/pdf/2010.07576
5	EMNLP2020	Logic2Text: High-Fidelity Natural Language Generation from Logical Forms		https://github.com/czyssrs/Logic2Text	https://arxiv.org/pdf/2004.14579
6	EMNLP2020	Composed Variational Natural Language Generation for Few-shot Intents			https://arxiv.org/pdf/2009.10056
7	EMNLP2020	Continual Learning for Natural Language Generation in Task-oriented Dialog Systems			https://arxiv.org/pdf/2010.00910
8	EMNLP2020	Dual Inference for Improving Language Understanding and Generation		https://github.com/MiuLab/DuaLUG	https://arxiv.org/pdf/2010.04246
9	EMNLP2019	Neural data-to-text generation: A comparison between pipeline and end- to-end architectures		https://github.com/ThiagoCF05/webnlg	https://arxiv.org/pdf/1908.09022
10	EMNLP2019	MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance			https://arxiv.org/pdf/1909.02622
11	EMNLP2019	Select and Attend: Towards Controllable Content Selection in Text Generation		https://github.com/chin-gyou/controllable-selection	https://arxiv.org/pdf/1909.04453
12	EMNLP2019	Knowledge Aware Conversation Generation with Explainable Reasoning over Augmented Graphs		https://github.com/PaddlePaddle/Research/tree/master/NLP/EMNLP2019-AKGCM	https://arxiv.org/pdf/1903.10245
13	EMNLP2019	Autoregressive Text Generation Beyond Feedback Loops		https://github.com/schmiflo/crf-generation	https://arxiv.org/pdf/1908.11658
14	EMNLP2019	ARAML: A Stable Adversarial Training Framework for Text Generation		https://github.com/kepei1106/ARAML	https://arxiv.org/pdf/1908.07195
15	EMNLP2019	Judge the Judges: A Large-Scale Evaluation Study of Neural Language Models for Online Review Generation		https://github.com/Crista23/JudgeTheJudges	https://arxiv.org/pdf/1901.00398

NAACL

序号	会议/期刊	论文	主要技术	代码	论文下载地址
1	NAACL2021	APo-VAE: Text Generation in Hyperbolic Space			https://arxiv.org/pdf/2005.00054
2	NAACL2021	FUDGE: Controlled Text Generation With Future Discriminators		https://github.com/yangkevin2/naacl-2021-fudge-controlled-generation	https://arxiv.org/pdf/2104.05218
3	NAACL2021	NeuroLogic Decoding: (Un)supervised Neural Text Generation with Predicate Logic Constraints			https://arxiv.org/pdf/2010.12884
4	NAACL2021	Plot-guided Adversarial Example Construction for Evaluating Open-domain Story Generation		https://github.com/PlusLabNLP/Plot-guided-Coherence-Evaluation	https://arxiv.org/pdf/2104.05801
5	NAACL2021	Progressive Generation of Long Text with Pretrained Language Models		https://github.com/tanyuqian/progressive-generation	https://arxiv.org/pdf/2006.15720
6	NAACL2021	OodGAN: Generative Adversarial Network for Out-of-Domain Data Generation			https://arxiv.org/pdf/2104.02484
7	NAACL2019	Jointly Optimizing Diversity and Relevance in Neural Response Generation			https://arxiv.org/pdf/1902.11205
8	NAACL2019	Neural Text Generation from Rich Semantic Representations		https://github.com/shlurbee/dmrs-text-generation-naacl2019	https://arxiv.org/pdf/1904.11564
9	NAACL2019	Text Generation from Knowledge Graphs with Graph Transformers		https://github.com/rikdz/GraphWriter	https://arxiv.org/pdf/1904.02342
10	NAACL2019	Text Generation with Exemplar-based Adaptive Decoding			https://arxiv.org/pdf/1904.04428
11	NAACL2019	Accelerated Reinforcement Learning for Sentence Generation by Vocabulary Prediction		https://github.com/hassyGo/NLG-RL	https://arxiv.org/pdf/1809.01694
12	NAACL2019	Pre-trained language model representations for language generation		https://github.com/pytorch/fairseq	https://arxiv.org/pdf/1903.09722
13	NAACL2019	Pragmatically Informative Text Generation			https://arxiv.org/pdf/1904.01301
14	NAACL2019	Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation		https://github.com/HareeshBahuleyan/probabilistic_nlg	https://arxiv.org/pdf/1806.08462

COLING

序号	会议/期刊	论文	主要技术	代码	论文下载地址
1	COLING2020	Affective Text Generation		https://github.com/ishikasingh/Affective-text-gen	https://arxiv.org/pdf/2011.04000
2	COLING2020	Curious Case of Language Generation Evaluation Metrics: A Cautionary Tale			https://arxiv.org/pdf/2010.13588
3	COLING2020	Facts2Story: Controlling Text Generation by Key Facts			https://arxiv.org/pdf/2012.04332
4	COLING2020	Vec2Sent: Probing Sentence Embeddings with Natural Language Generation			https://arxiv.org/pdf/2011.00592

摘要

ACL

序号	会议/期刊	论文	主要技术	代码	论文下载地址
1	ACL2021	Cross-Lingual Abstractive Summarization with Limited Parallel Resources		https://github.com/WoodenWhite/MCLAS	https://arxiv.org/pdf/2105.13648
2	ACL2021	Improving Factual Consistency of Abstractive Summarization via Question Answering			https://arxiv.org/pdf/2105.04623
3	ACL2021	Long-Span Summarization via Local Attention and Content Selection		https://github.com/potsawee/longsum0	https://arxiv.org/pdf/2105.03801
4	ACL2021	TWAG: A Topic-Guided Wikipedia Abstract Generator		https://github.com/THU-KEG/TWAG	https://arxiv.org/pdf/2106.15135
5	ACL2021	Language Model as an Annotator: Exploring DialoGPT for Dialogue Summarization		https://github.com/xcfcode/PLM_annotator	https://arxiv.org/pdf/2105.12544
6	ACL2021	BASS: Boosting Abstractive Summarization with Unified Semantic Graph			https://arxiv.org/pdf/2105.12041
7	ACL2021	Focus Attention: Promoting Faithfulness and Diversity in Summarization			https://arxiv.org/pdf/2105.11921
8	ACL2021	Generating Query Focused Summaries from Query-Free Resources		https://github.com/yumoxu/marge	https://arxiv.org/pdf/2012.14774
9	ACL2021	ConvoSumm: Conversation Summarization Benchmark and Improved Abstractive Summarization with Argument Mining		https://github.com/Yale-LILY/ConvoSumm	https://arxiv.org/pdf/2106.00829
10	ACL2020	On Faithfulness and Factuality in Abstractive Summarization		https://github.com/google-research-datasets/xsum_hallucination_annotations	https://arxiv.org/pdf/2005.00661
11	ACL2020	FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization		https://github.com/esdurmus/summary-faithfulness	https://arxiv.org/pdf/2005.03754
12	ACL2020	On Faithfulness and Factuality in Abstractive Summarization		https://github.com/google-research-datasets/xsum_hallucination_annotations	https://arxiv.org/pdf/2005.00661
13	ACL2020	Knowledge Graph-Augmented Abstractive Summarization with Semantic-Driven Cloze Reward		https://github.com/luyang-huang96/GraphAugmentedSum	https://arxiv.org/pdf/2005.01159
14	ACL2020	The Summary Loop: Learning to Write Abstractive Summaries Without Examples		https://github.com/cannylab/summary_loop	https://arxiv.org/pdf/2105.05361
15	ACL2020	Leveraging Graph to Improve Abstractive Multi-Document Summarization		https://github.com/PaddlePaddle/Research	https://arxiv.org/pdf/2005.10043
16	ACL2019	Scoring Sentence Singletons and Pairs for Abstractive Summarization		https://github.com/ucfnlp/summarization-sing-pair-mix	https://arxiv.org/pdf/1906.00077

EMNLP

序号	会议/期刊	论文	主要技术	代码	论文下载地址
1	EMNLP2020	A Hierarchical Network for Abstractive Meeting Summarization with Cross- Domain Pretraining		https://github.com/microsoft/HMNet	https://arxiv.org/pdf/2004.02016
2	EMNLP2020	Conditional Neural Generation using Sub-Aspect Functions for Extractive News Summarization			https://arxiv.org/pdf/2004.13983
3	EMNLP2020	Unsupervised Extractive Summarization by Pre-training Hierarchical Transformers		https://github.com/xssstory/STAS	https://arxiv.org/pdf/2010.08242
4	EMNLP2020	Corpora Evaluation and System Bias detection in Multi Document Summarization		https://github.com/LCS2-IIITD/summarization_bias	https://arxiv.org/pdf/2010.01786
5	EMNLP2020	An Empirical Study of Cross-Dataset Evaluation for Neural Summarization Systems		https://github.com/zide05/CDEvalSumm	https://arxiv.org/pdf/2010.05139
6	EMNLP2019	Contrastive Attention Mechanism for Abstractive Sentence Summarization		https://github.com/travel-go/Abstractive-Text-Summarization	https://arxiv.org/pdf/1910.13114
7	EMNLP2019	Concept Pointer Network for Abstractive Summarization		https://github.com/wprojectsn/codes	https://arxiv.org/pdf/1910.08486
8	EMNLP2019	Contrastive Attention Mechanism for Abstractive Sentence Summarization		https://github.com/travel-go/Abstractive-Text-Summarization	https://arxiv.org/pdf/1910.13114
9	EMNLP2019	Neural Extractive Text Summarization with Syntactic Compression			https://arxiv.org/pdf/1902.00863
10	EMNLP2019	Text Summarization with Pretrained Encoders		https://github.com/nlpyang/PreSumm	https://arxiv.org/pdf/1908.08345

NAACL

序号	会议/期刊	论文	主要技术	代码	论文下载地址
1	NAACL2021	GSum: A General Framework for Guided Neural Abstractive Summarization		https://github.com/neulab/guided_summarization	https://arxiv.org/pdf/2010.08014
2	NAACL2021	Improving Zero and Few-Shot Abstractive Summarization with Intermediate Fine- tuning and Data Augmentation			https://arxiv.org/pdf/2010.12836
3	NAACL2021	Structure-Aware Abstractive Conversation Summarization via Discourse and Action Graphs		https://github.com/GT-SALT/Structure-Aware-BART	https://arxiv.org/pdf/2104.08400
4	NAACL2021	AdaptSum: Towards Low-Resource Domain Adaptation for Abstractive Summarization		https://github.com/TysonYu/AdaptSum	https://arxiv.org/pdf/2103.11332
5	NAACL2021	A New Approach to Overgenerating and Scoring Abstractive Summaries		https://github.com/ucfnlp/varying-length-summ	https://arxiv.org/pdf/2104.01726
6	NAACL2021	Improving Faithfulness in Abstractive Summarization with Contrast Candidate Generation and Selection			https://arxiv.org/pdf/2104.09061
7	NAACL2021	Enriching Transformers with Structured Tensor-Product Representations for Abstractive Summarization		https://github.com/jiangycTarheel/TPT-Summ	https://arxiv.org/pdf/2106.01317
8	NAACL2021	Attention Head Masking for Inference Time Content Selection in Abstractive Summarization			https://arxiv.org/pdf/2104.02205
9	NAACL2021	Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics		https://github.com/artidoro/frank	https://arxiv.org/pdf/2104.13346

COLING

序号	会议/期刊	论文	主要技术	代码	论文下载地址
1	COLING2020	How Domain Terminology Affects Meeting Summarization Performance		https://github.com/ucfnlp/meeting-domain-terminology	https://arxiv.org/pdf/2011.00692
2	COLING2020	Fact-level Extractive Summarization with Hierarchical Graph Mask on BERT		https://github.com/Ruifeng-paper/FactExsum-coling2020	https://arxiv.org/pdf/2011.09739
3	COLING2020	WSL-DS: Weakly Supervised Learning with Distant Supervision for Query Focused Multi-Document Abstractive Summarization		https://github.com/tahmedge/WSL-DS-COLING-2020	https://arxiv.org/pdf/2011.01421