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Found 46 papers, 14 papers with code
A Numerical Reasoning Question Answering System with Fine-grained Retriever and the Ensemble of Multiple Generators for FinQA
Here, we propose a numerical reasoning question answering system to answer numerical reasoning questions among financial text and table data sources, consisting of a retriever module, a generator module, and an ensemble module.
Modeling Users' Contextualized Page-wise Feedback for Click-Through Rate Prediction in E-commerce Search
In this paper, we propose a new perspective for context-aware users' behavior modeling by including the whole page-wisely exposed products and the corresponding feedback as contextualized page-wise feedback sequence.
Synonym Knowledge Enhanced Reader for Chinese Idiom Reading Comprehension
Machine reading comprehension (MRC) is the task that asks a machine to answer questions based on a given context.
Alleviating the Inequality of Attention Heads for Neural Machine Translation
Recent studies show that the attention heads in Transformer are not equal.
Ranked #1 on
Machine Translation
on WMT2017 Turkish-English
Prompt Agnostic Essay Scorer: A Domain Generalization Approach to Cross-prompt Automated Essay Scoring
Cross-prompt automated essay scoring (AES) requires the system to use non target-prompt essays to award scores to a target-prompt essay.
Dialogue State Tracking with Explicit Slot Connection Modeling
Recent proposed approaches have made promising progress in dialogue state tracking (DST).
Explicit Semantic Decomposition for Definition Generation
Definition generation, which aims to automatically generate dictionary definitions for words, has recently been proposed to assist the construction of dictionaries and help people understand unfamiliar texts.
Mirror-Generative Neural Machine Translation
Training neural machine translation models (NMT) requires a large amount of parallel corpus, which is scarce for many language pairs.
Adding A Filter Based on The Discriminator to Improve Unconditional Text Generation
To alleviate the exposure bias, generative adversarial networks (GAN) use the discriminator to update the generator's parameters directly, but they fail by being evaluated precisely.
R3: A Reading Comprehension Benchmark Requiring Reasoning Processes
Existing question answering systems can only predict answers without explicit reasoning processes, which hinder their explainability and make us overestimate their ability of understanding and reasoning over natural language.
Latent Opinions Transfer Network for Target-Oriented Opinion Words Extraction
In this paper, we propose a novel model to transfer these opinions knowledge from resource-rich review sentiment classification datasets to low-resource task TOWE.
Aspect-oriented Opinion Extraction
General Classification
+3
Generating Diverse Translation by Manipulating Multi-Head Attention
Experiments also show that back-translation with these diverse translations could bring significant improvement on performance on translation tasks.
A Reinforced Generation of Adversarial Examples for Neural Machine Translation
Neural machine translation systems tend to fail on less decent inputs despite its significant efficacy, which may significantly harm the credibility of this systems-fathoming how and when neural-based systems fail in such cases is critical for industrial maintenance.
Multi-Perspective Inferrer: Reasoning Sentences Relationship from Holistic Perspective
Intuitively, NLI should rely more on multiple perspectives to form a holistic view to eliminate bias.
Pre-train and Learn: Preserve Global Information for Graph Neural Networks
Graph neural networks (GNNs) have shown great power in learning on attributed graphs.
Fine-grained Knowledge Fusion for Sequence Labeling Domain Adaptation
In sequence labeling, previous domain adaptation methods focus on the adaptation from the source domain to the entire target domain without considering the diversity of individual target domain samples, which may lead to negative transfer results for certain samples.
GeoSQA: A Benchmark for Scenario-based Question Answering in the Geography Domain at High School Level
Scenario-based question answering (SQA) has attracted increasing research attention.
Generating Sentences from Disentangled Syntactic and Semantic Spaces
In this paper, we propose to generate sentences from disentangled syntactic and semantic spaces.
Target-oriented Opinion Words Extraction with Target-fused Neural Sequence Labeling
In this paper, we propose a novel sequence labeling subtask for ABSA named TOWE (Target-oriented Opinion Words Extraction), which aims at extracting the corresponding opinion words for a given opinion target.
Aspect-Based Sentiment Analysis
Aspect-oriented Opinion Extraction
+2
Online Distilling from Checkpoints for Neural Machine Translation
Our method on-the-fly generates a teacher model from checkpoints, guiding the training process to obtain better performance.
Exploiting Noisy Data in Distant Supervision Relation Classification
Distant supervision has obtained great progress on relation classification task.
Adversarial Sub-sequence for Text Generation
It is easy to improve the existing GAN-based models with this mechanism.
Dynamic Past and Future for Neural Machine Translation
Previous studies have shown that neural machine translation (NMT) models can benefit from explicitly modeling translated (Past) and untranslated (Future) to groups of translated and untranslated contents through parts-to-wholes assignment.
Learning to Discriminate Noises for Incorporating External Information in Neural Machine Translation
Previous studies show that incorporating external information could improve the translation quality of Neural Machine Translation (NMT) systems.
Combining Character and Word Information in Neural Machine Translation Using a Multi-Level Attention
Natural language sentences, being hierarchical, can be represented at different levels of granularity, like words, subwords, or characters.
Collaborative Filtering with Topic and Social Latent Factors Incorporating Implicit Feedback
First, we propose a novel model {\em \mbox{MR3}} to jointly model three sources of information (i. e., ratings, item reviews, and social relations) effectively for rating prediction by aligning the latent factors and hidden topics.
Improving Review Representations with User Attention and Product Attention for Sentiment Classification
Recently, some works achieved improvement by incorporating user and product information to generate a review representation.
Ranked #3 on
Sentiment Analysis
on User and product information
Modeling Past and Future for Neural Machine Translation
The Past and Future contents are fed to both the attention model and the decoder states, which offers NMT systems the knowledge of translated and untranslated contents.
Dynamic Oracle for Neural Machine Translation in Decoding Phase
However, there are certain limitations in Scheduled Sampling and we propose two dynamic oracle-based methods to improve it.
Word-Context Character Embeddings for Chinese Word Segmentation
Neural parsers have benefited from automatically labeled data via dependency-context word embeddings.
Neural Machine Translation with Word Predictions
In the encoder-decoder architecture for neural machine translation (NMT), the hidden states of the recurrent structures in the encoder and decoder carry the crucial information about the sentence. These vectors are generated by parameters which are updated by back-propagation of translation errors through time.
Top-Rank Enhanced Listwise Optimization for Statistical Machine Translation
We propose a listwise learning framework for structure prediction problems such as machine translation.
Going Wider: Recurrent Neural Network With Parallel Cells
Recurrent Neural Network (RNN) has been widely applied for sequence modeling.
Integrating Reviews into Personalized Ranking for Cold Start Recommendation
On top of text features we uncover the review dimensions that explain the variation in users' feedback and these review factors represent a prior preference of users.
Evaluating a Deterministic Shift-Reduce Neural Parser for Constituent Parsing
Greedy transition-based parsers are appealing for their very fast speed, with reasonably high accuracies.
A Synthetic Approach for Recommendation: Combining Ratings, Social Relations, and Reviews
Recommender systems (RSs) provide an effective way of alleviating the information overload problem by selecting personalized choices.
Topic2Vec: Learning Distributed Representations of Topics
Latent Dirichlet Allocation (LDA) mining thematic structure of documents plays an important role in nature language processing and machine learning areas.
Non-linear Learning for Statistical Machine Translation
The linear combination assumes that all the features are in a linear relationship and constrains that each feature interacts with the rest features in an linear manner, which might limit the expressive power of the model and lead to a under-fit model on the current data.
