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TitleStatusHype
Natural Language and Spatial Rules—0
An analysis of document graph construction methods for AMR summarization—0
Simple Contrastive Representation Adversarial Learning for NLP Tasks—0
PSSL: Self-supervised Learning for Personalized Search with Contrastive SamplingCode0
S-SimCSE: Sampled Sub-networks for Contrastive Learning of Sentence Embedding—0
Vector Space Semantics for Lambek Calculus with Soft Subexponentials—0
Isomer: Transfer enhanced Dual-Channel Heterogeneous Dependency Attention Network for Aspect-based Sentiment Classification—0
Building a Question Answering System for the Manufacturing Domain—0
DVCFlow: Modeling Information Flow Towards Human-like Video Captioning—0
How much do language models copy from their training data? Evaluating linguistic novelty in text generation using RAVEN—0
MEDCOD: A Medically-Accurate, Emotive, Diverse, and Controllable Dialog System—0
High Quality Rather than High Model Probability: Minimum Bayes Risk Decoding with Neural Metrics—0
High Quality Streaming Speech Synthesis with Low, Sentence-Length-Independent Latency—0
DiverGAN: An Efficient and Effective Single-Stage Framework for Diverse Text-to-Image Generation—0
Sentence-Level Discourse Parsing as Text-to-Text Generation—0
Effective Unsupervised Constrained Text Generation based on Perturbed Masking—0
Are All the Datasets in Benchmark Necessary? A Pilot Study of Dataset Evaluation for Text ClassificationCode0
Sentence-level Privacy for Document Embeddings—0
Improving Neural Models for Radiology Report Retrieval with Lexicon-based Automated Annotation—0
RoMe: A Robust Metric for Evaluating Natural Language Generation—0
NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction—0
NSP-NER: A Prompt-based Learner for Few-shot NER Driven by Next Sentence Prediction—0
Learning Universal Sentence Embeddings with Large-scale Parallel Translation Datasets—0
Co-training an Unsupervised Constituency Parser with Weak Supervision—0
Sequence-to-sequence AMR Parsing with Ancestor Information—0
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