Informativeness
244 papers with code • 1 benchmarks • 1 datasets
Libraries
Use these libraries to find Informativeness models and implementations
CrisisMMD
Most implemented papers
Learning to Navigate for Fine-grained Classification
yangze0930/NTS-Net
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ECCV 2018
In consideration of intrinsic consistency between informativeness of the regions and their probability being ground-truth class, we design a novel training paradigm, which enables Navigator to detect most informative regions under the guidance from Teacher.
NRPA: Neural Recommendation with Personalized Attention
In this paper we propose a neural recommendation approach with personalized attention to learn personalized representations of users and items from reviews.
Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular Maximization
We introduce a novel graph-based framework for abstractive meeting speech summarization that is fully unsupervised and does not rely on any annotations.
Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization
dreasysnail/converse_GAN
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NeurIPS 2018
Responses generated by neural conversational models tend to lack informativeness and diversity.
Large Language Models Are Human-Level Prompt Engineers
By conditioning on natural language instructions, large language models (LLMs) have displayed impressive capabilities as general-purpose computers.
Response Generation by Context-aware Prototype Editing
Open domain response generation has achieved remarkable progress in recent years, but sometimes yields short and uninformative responses.
BARTScore: Evaluating Generated Text as Text Generation
In this work, we conceptualize the evaluation of generated text as a text generation problem, modeled using pre-trained sequence-to-sequence models.
Dataset Distillation via Factorization
huage001/datasetfactorization
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In this paper, we study \xw{dataset distillation (DD)}, from a novel perspective and introduce a \emph{dataset factorization} approach, termed \emph{HaBa}, which is a plug-and-play strategy portable to any existing DD baseline.
Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systems
andy194673/nlg-sclstm-multiwoz
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EMNLP 2015
Natural language generation (NLG) is a critical component of spoken dialogue and it has a significant impact both on usability and perceived quality.
Prosody Modifications for Question-Answering in Voice-Only Settings
Many popular form factors of digital assistants---such as Amazon Echo, Apple Homepod, or Google Home---enable the user to hold a conversation with these systems based only on the speech modality.
