nyu-dl / dl4mt-seqgen

Related projects: ⓘ

• duorc / duorc
  A Large-Scale Dataset for Paraphrased Reading Comprehension
  ☆16Updated last year
• chinnadhurai / ParlAI
  A framework for training and evaluating AI models on a variety of openly available dialogue datasets.
  ☆36Updated 4 years ago
• xinyadu / harvestingQA
  ☆60Updated 6 years ago
• ZeweiChu / MQR
  ☆20Updated 4 years ago
• xwhan / ProQA
  Progressively Pretrained Dense Corpus Index for Open-Domain QA and Information Retrieval
  ☆43Updated last year
• liufly / refreader
  The Referential Reader: A Recurrent Entity Network for Anaphora Resolution, published at ACL 2019
  ☆19Updated 4 years ago
• vzhong / e3
  Dockerized code for E3: Entailment-driven Extracting and Editing for Conversational Machine Reading.
  ☆48Updated last year
• jxhe / self-training-text-generation
  Implementation of ICLR 2020 paper "Revisiting Self-Training for Neural Sequence Generation"
  ☆47Updated 2 years ago
• ZhitingHu / text_content_manipulation
  Text Content Manipulation
  ☆45Updated 3 years ago
• sheng-z / cross-lingual-open-ie
  MT/IE: Cross-lingual Open Information Extraction with Neural Sequence-to-Sequence Models
  ☆22Updated 6 years ago
• jiacheng-xu / text-sum-uncertainty
  Code for "Understanding Neural Abstractive Summarization Models via Uncertainty" (EMNLP20)
  ☆30Updated 3 years ago
• jiaweiw / Extract-Edit-Unsupervised-NMT
  ☆25Updated this week
• hhexiy / debiased
  Learn models that are robust to spurious correlations in the dataset.
  ☆23Updated 4 years ago
• UriSha / EmbeddinglessNMT
  The implementation of "Neural Machine Translation without Embeddings", NAACL 2021
  ☆33Updated 3 years ago
• easonnie / semanticRetrievalMRS
  This is the repo for the paper "Revealing the Importance of Semantic Retrieval for Machine Reading at Scale".
  ☆59Updated 4 years ago
• chin-gyou / improving-variational-encoder-decoders-in-dialogue-generation
  Tensorflow Implementation of Improving Variational Encoder-Decoders in Dialogue Generation
  ☆27Updated 6 years ago
• bohanli / vae-pretraining-encoder
  PyTorch implementation of A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text (EMNLP 2019)
  ☆46Updated 4 years ago
• MysteryVaibhav / robust_mtnt
  Code for the paper "Improving Robustness of Machine Translation with Synthetic Noise"
  ☆21Updated 4 years ago
• MiuLab / HNLG
  Natural Language Generation by Hierarchical Decoding with Linguistic Patterns (NAACL-HLT 2018), Investigating Linguistic Pattern Ordering…
  ☆33Updated 5 years ago
• misonuma / strsum
  A code for "Unsupervised Neural Single-Document Summarization of Reviews via Learning Latent Discourse Structure and its Ranking" in ACL2…
  ☆27Updated 5 years ago
• mingdachen / vsl
  Code for "Variational Sequential Labelers for Semi-Supervised Learning" (EMNLP 2018)
  ☆34Updated 5 years ago
• mingdachen / syntactic-template-generation
  Code for "Controllable Paraphrase Generation with a Syntactic Exemplar" (ACL 2019)
  ☆79Updated 4 years ago
• zhengzx-nlp / past-and-future-nmt
  Implementation of "Modeling Past and Future for Neural Machine Translation"
  ☆15Updated 6 years ago
• lanwuwei / Twitter-URL-Corpus
  Large scale sentential paraphrases collection and annotation
  ☆47Updated last year
• wenhuchen / Variational-Vocabulary-Selection
  Code for NAACL19 Paper "How Large a Vocabulary Does Text Classification Need? A Variational Approach to Vocabulary Selection"
  ☆42Updated 5 years ago
• boknilev / nlp-analysis-methods
  Companion site for "Analysis Methods in Neural Language Processing: A Survey"
  ☆67Updated 4 years ago
• decompositional-semantics-initiative / DNC
  Diverse Natural Language Inference Collection - NLI dataset that can used to evaluate how well models perform distinct types of reasoning…
  ☆36Updated 3 years ago
• shrimai / Towards-Content-Transfer-through-Grounded-Text-Generation
  ☆34Updated 5 years ago
• thespectrewithin / joint_align
  Cross-lingual Alignment vs Joint Training: A Comparative Study and A Simple Unified Framework
  ☆52Updated 4 years ago
• qkaren / converse_reading_cmr
  code, data, and model for ACL-19 paper "Conversing by Reading: Contentful Neural Conversation with On-demand Machine Reading"
  ☆77Updated 3 years ago