Multi-modal keyphrase generation aims to produce a set of keyphrases tha...
Multi-choice questions (MCQs) serve as a common yet important task forma...
Large Language Models (LLMs) present strong general capabilities, and a
...
Large language models (LLMs) are capable of performing conditional seque...
Catastrophic forgetting (CF) is a phenomenon that occurs in machine lear...
N-gram matching-based evaluation metrics, such as BLEU and chrF, are wid...
As large language models (LLMs) generate texts with increasing fluency a...
Open-sourced large language models (LLMs) have demonstrated remarkable
e...
Multilingual pre-trained language models have demonstrated impressive
(z...
In-context learning (ICL) emerges as a promising capability of large lan...
Many-to-many multimodal summarization (M^3S) task aims to generate
summa...
Task-incremental continual learning refers to continually training a mod...
Comprehending characters' personalities is a crucial aspect of story rea...
To adapt text summarization to the multilingual world, previous work pro...
Multilingual vision-language (V L) pre-training has achieved remarkabl...
In this paper, we introduce WeLayout, a novel system for segmenting the
...
Representation forgetting refers to the drift of contextualized
represen...
Pre-trained Language Models (PLMs) may be poisonous with backdoors or bi...
Recently, DeepNorm scales Transformers into extremely deep (i.e., 1000
l...
Existing neural machine translation (NMT) studies mainly focus on develo...
Recently, the emergence of ChatGPT has attracted wide attention from the...
Given a document in a source language, cross-lingual summarization (CLS)...
Neural chat translation (NCT) aims to translate a cross-lingual chat bet...
Federated Learning (FL) has become a popular distributed learning paradi...
The goal of multimodal abstractive summarization (MAS) is to produce a
c...
Given a document in a source language, cross-lingual summarization (CLS)...
Minimum Bayesian Risk Decoding (MBR) emerges as a promising decoding
alg...
We report the result of the first edition of the WMT shared task on
Tran...
This paper introduces WeChat's participation in WMT 2022 shared biomedic...
This paper introduces the joint submission of the Beijing Jiaotong Unive...
Chinese Spelling Correction (CSC) is a task to detect and correct spelli...
In this work, we focus on dialogue reading comprehension (DRC), a task
e...
Empathy, which is widely used in psychological counselling, is a key tra...
k-Nearest-Neighbor Machine Translation (kNN-MT) becomes an important res...
Modern neural machine translation (NMT) models have achieved competitive...
Despite the remarkable success of pre-trained language models (PLMs), th...
Visual Question Answering (VQA) models are prone to learn the shortcut
s...
Models for Visual Question Answering (VQA) often rely on the spurious
co...
Word alignment which aims to extract lexicon translation equivalents bet...
Word-level Quality Estimation (QE) of Machine Translation (MT) aims to f...
Hallucination, one kind of pathological translations that bothers Neural...
Neural Chat Translation (NCT) aims to translate conversational text into...
Conversational Causal Emotion Entailment aims to detect causal utterance...
Recent studies on the lottery ticket hypothesis (LTH) show that pre-trai...
Generating adversarial examples for Neural Machine Translation (NMT) wit...
Cross-lingual summarization is the task of generating a summary in one
l...
Visual dialog has witnessed great progress after introducing various
vis...
The goal of the cross-lingual summarization (CLS) is to convert a docume...
Although pre-trained sequence-to-sequence models have achieved great suc...
Token-level adaptive training approaches can alleviate the token imbalan...