research
∙
08/09/2023
Extrapolating Large Language Models to Non-English by Aligning Languages
Due to the unbalanced training data distribution, the language ability o...
share
research
∙
08/06/2023
Food-500 Cap: A Fine-Grained Food Caption Benchmark for Evaluating Vision-Language Models
Vision-language models (VLMs) have shown impressive performance in subst...
research
∙
07/06/2023
BLEURT Has Universal Translations: An Analysis of Automatic Metrics by Minimum Risk Training
Automatic metrics play a crucial role in machine translation. Despite th...
research
∙
06/10/2023
INK: Injecting kNN Knowledge in Nearest Neighbor Machine Translation
Neural machine translation has achieved promising results on many transl...
research
∙
05/24/2023
Eliciting the Translation Ability of Large Language Models via Multilingual Finetuning with Translation Instructions
Large-scale Pretrained Language Models (LLMs), such as ChatGPT and GPT4,...
research
∙
04/10/2023
Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis
Large language models (LLMs) have demonstrated remarkable potential in h...
research
∙
03/31/2023
Selective Knowledge Distillation for Non-Autoregressive Neural Machine Translation
Benefiting from the sequence-level knowledge distillation, the Non-Autor...
research
∙
02/27/2023
kNN-BOX: A Unified Framework for Nearest Neighbor Generation
Augmenting the base neural model with a token-level symbolic datastore i...
research
∙
12/17/2022
Better Datastore, Better Translation: Generating Datastores from Pre-Trained Models for Nearest Neural Machine Translation
Nearest Neighbor Machine Translation (kNNMT) is a simple and effective m...
research
∙
12/03/2022
CoP: Factual Inconsistency Detection by Controlling the Preference
Abstractive summarization is the process of generating a summary given a...
research
∙
11/11/2022
Helping the Weak Makes You Strong: Simple Multi-Task Learning Improves Non-Autoregressive Translators
Recently, non-autoregressive (NAR) neural machine translation models hav...
research
∙
11/08/2022
What Knowledge Is Needed? Towards Explainable Memory for kNN-MT Domain Adaptation
kNN-MT presents a new paradigm for domain adaptation by building an exte...
research
∙
10/22/2022
Structure-Unified M-Tree Coding Solver for MathWord Problem
As one of the challenging NLP tasks, designing math word problem (MWP) s...
research
∙
10/18/2022
Probing Cross-modal Semantics Alignment Capability from the Textual Perspective
In recent years, vision and language pre-training (VLP) models have adva...
research
∙
09/23/2022
Zero-shot Domain Adaptation for Neural Machine Translation with Retrieved Phrase-level Prompts
Domain adaptation is an important challenge for neural machine translati...
research
∙
06/17/2022
A Numerical Reasoning Question Answering System with Fine-grained Retriever and the Ensemble of Multiple Generators for FinQA
The numerical reasoning in the financial domain – performing quantitativ...
research
∙
04/20/2022
Analyzing the Intensity of Complaints on Social Media
Complaining is a speech act that expresses a negative inconsistency betw...
research
∙
04/05/2022
latent-GLAT: Glancing at Latent Variables for Parallel Text Generation
Recently, parallel text generation has received widespread attention due...
research
∙
09/23/2021
Non-Parametric Online Learning from Human Feedback for Neural Machine Translation
We study the problem of online learning with human feedback in the human...
research
∙
09/21/2021
Learning Kernel-Smoothed Machine Translation with Retrieved Examples
How to effectively adapt neural machine translation (NMT) models accordi...
research
∙
09/14/2021
Non-Parametric Unsupervised Domain Adaptation for Neural Machine Translation
Recently, kNN-MT has shown the promising capability of directly incorpor...
research
∙
07/27/2021
Energy-based Unknown Intent Detection with Data Manipulation
Unknown intent detection aims to identify the out-of-distribution (OOD) ...
research
∙
05/27/2021
Adaptive Nearest Neighbor Machine Translation
kNN-MT, recently proposed by Khandelwal et al. (2020a), successfully com...
research
∙
05/15/2021
DirectQE: Direct Pretraining for Machine Translation Quality Estimation
Machine Translation Quality Estimation (QE) is a task of predicting the ...
research
∙
05/07/2021
Duplex Sequence-to-Sequence Learning for Reversible Machine Translation
Sequence-to-sequence (seq2seq) problems such as machine translation are ...
research
∙
03/21/2021
Non-Autoregressive Translation by Learning Target Categorical Codes
Non-autoregressive Transformer is a promising text generation model. How...
research
∙
03/16/2021
Dual Side Deep Context-aware Modulation for Social Recommendation
Social recommendation is effective in improving the recommendation perfo...
research
∙
12/31/2020
FDMT: A Benchmark Dataset for Fine-grained Domain Adaptation in Machine Translation
Previous domain adaptation research usually neglect the diversity in tra...
research
∙
11/30/2020
A Simple and Effective Approach to Robust Unsupervised Bilingual Dictionary Induction
Unsupervised Bilingual Dictionary Induction methods based on the initial...
research
∙
11/01/2020
Transformer-based Multi-Aspect Modeling for Multi-Aspect Multi-Sentiment Analysis
Aspect-based sentiment analysis (ABSA) aims at analyzing the sentiment o...
research
∙
11/01/2020
Opinion Transmission Network for Jointly Improving Aspect-oriented Opinion Words Extraction and Sentiment Classification
Aspect-level sentiment classification (ALSC) and aspect oriented opinion...
research
∙
10/18/2020
Capturing Longer Context for Document-level Neural Machine Translation: A Multi-resolutional Approach
Discourse context has been proven useful when translating documents. It ...
research
∙
09/21/2020
Alleviating the Inequality of Attention Heads for Neural Machine Translation
Recent studies show that the attention heads in Transformer are not equa...
research
∙
08/04/2020
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 no...
research
∙
05/16/2020
RPD: A Distance Function Between Word Embeddings
It is well-understood that different algorithms, training processes, and...
research
∙
02/24/2020
GRET: Global Representation Enhanced Transformer
Transformer, based on the encoder-decoder framework, has achieved state-...
research
∙
02/19/2020
Toward Making the Most of Context in Neural Machine Translation
Document-level machine translation manages to outperform sentence level ...
research
∙
01/07/2020
Latent Opinions Transfer Network for Target-Oriented Opinion Words Extraction
Target-oriented opinion words extraction (TOWE) is a new subtask of ABSA...
research
∙
12/04/2019
Acquiring Knowledge from Pre-trained Model to Neural Machine Translation
Pre-training and fine-tuning have achieved great success in the natural ...
research
∙
11/25/2019
Non-autoregressive Transformer by Position Learning
Non-autoregressive models are promising on various text generation tasks...
research
∙
11/21/2019
Generating Diverse Translation by Manipulating Multi-Head Attention
Transformer model has been widely used on machine translation tasks and ...
research
∙
11/09/2019
A Reinforced Generation of Adversarial Samples for Neural Machine Translation
Neural machine translation systems tend to fail on less de-cent inputs d...
research
∙
11/09/2019
Multi-Perspective Inferrer: Reasoning Sentences Relationship from Holistic Perspective
Natural Language Inference (NLI) aims to determine the logic relationshi...
research
∙
09/10/2019
Fine-grained Knowledge Fusion for Sequence Labeling Domain Adaptation
In sequence labeling, previous domain adaptation methods focus on the ad...
research
∙
08/21/2019
Improving Neural Machine Translation with Pre-trained Representation
Monolingual data has been demonstrated to be helpful in improving the tr...
research
∙
07/17/2019
Learning Representation Mapping for Relation Detection in Knowledge Base Question Answering
Relation detection is a core step in many natural language process appli...
research
∙
07/08/2019
Correct-and-Memorize: Learning to Translate from Interactive Revisions
State-of-the-art machine translation models are still not on par with hu...
research
∙
07/06/2019
Generating Sentences from Disentangled Syntactic and Semantic Spaces
Variational auto-encoders (VAEs) are widely used in natural language gen...
research
∙
04/21/2019
Dynamic Past and Future for Neural Machine Translation
Previous studies have shown that neural machine translation (NMT) models...
research
∙
10/24/2018
