30 citations · 237 across the 51 of their papers we have counts for
52 papers
Emage: Non-Autoregressive Text-to-Image Generation
Zhangyin Feng, Runyi Hu, Liangxin Liu +7
Autoregressive and diffusion models drive the recent breakthroughs on text-to-image generation. Despite their huge success of generating high-realistic images, a common shortcoming…
Rethinking Word-Level Auto-Completion in Computer-Aided Translation
Xingyu Chen, Lemao Liu, Guoping Huang +4
Word-Level Auto-Completion (WLAC) plays a crucial role in Computer-Assisted Translation. It aims at providing word-level auto-completion suggestions for human translators. While pr…
On Synthetic Data for Back Translation
Jiahao Xu, Yubin Ruan, Wei Bi +4
Back translation (BT) is one of the most significant technologies in NMT research fields. Existing attempts on BT share a common characteristic: they employ either beam search or r…
IMTLab: An Open-Source Platform for Building, Evaluating, and Diagnosing Interactive Machine Translation Systems
Xu Huang, Zhirui Zhang, Ruize Gao +6
We present IMTLab, an open-source end-to-end interactive machine translation (IMT) system platform that enables researchers to quickly build IMT systems with state-of-the-art model…
GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher
Youliang Yuan, Wenxiang Jiao, Wenxuan Wang +4
Safety lies at the core of the development of Large Language Models (LLMs). There is ample work on aligning LLMs with human ethics and preferences, including data filtering in pret…
Disco-Bench: A Discourse-Aware Evaluation Benchmark for Language Modelling
Longyue Wang, Zefeng Du, Donghuai Liu +7
Modeling discourse -- the linguistic phenomena that go beyond individual sentences, is a fundamental yet challenging aspect of natural language processing (NLP). However, existing…
On the Cultural Gap in Text-to-Image Generation
Bingshuai Liu, Longyue Wang, Chenyang Lyu +4
One challenge in text-to-image (T2I) generation is the inadvertent reflection of culture gaps present in the training data, which signifies the disparity in generated image quality…
SkillNet-X: A Multilingual Multitask Model with Sparsely Activated Skills
Zhangyin Feng, Yong Dai, Fan Zhang +6
Traditional multitask learning methods basically can only exploit common knowledge in task- or language-wise, which lose either cross-language or cross-task knowledge. This paper p…
Explicit Syntactic Guidance for Neural Text Generation
Yafu Li, Leyang Cui, Jianhao Yan +4
Most existing text generation models follow the sequence-to-sequence paradigm. Generative Grammar suggests that humans generate natural language texts by learning language grammar.…
Macaw-LLM: Multi-Modal Language Modeling with Image, Audio, Video, and Text Integration
Chenyang Lyu, Minghao Wu, Longyue Wang +5
Although instruction-tuned large language models (LLMs) have exhibited remarkable capabilities across various NLP tasks, their effectiveness on other data modalities beyond text ha…
Rethinking Translation Memory Augmented Neural Machine Translation
Hongkun Hao, Guoping Huang, Lemao Liu +3
This paper rethinks translation memory augmented neural machine translation (TM-augmented NMT) from two perspectives, i.e., a probabilistic view of retrieval and the variance-bias…
Enhancing Grammatical Error Correction Systems with Explanations
Yuejiao Fei, Leyang Cui, Sen Yang +3
Grammatical error correction systems improve written communication by detecting and correcting language mistakes. To help language learners better understand why the GEC system mak…
Sen2Pro: A Probabilistic Perspective to Sentence Embedding from Pre-trained Language Model
Lingfeng Shen, Haiyun Jiang, Lemao Liu +1
Sentence embedding is one of the most fundamental tasks in Natural Language Processing and plays an important role in various tasks. The recent breakthrough in sentence embedding i…
Improved Visual Story Generation with Adaptive Context Modeling
Zhangyin Feng, Yuchen Ren, Xinmiao Yu +4
Diffusion models developed on top of powerful text-to-image generation models like Stable Diffusion achieve remarkable success in visual story generation. However, the best-perform…
A Survey on Zero Pronoun Translation
Longyue Wang, Siyou Liu, Mingzhou Xu +3
Zero pronouns (ZPs) are frequently omitted in pro-drop languages (e.g. Chinese, Hungarian, and Hindi), but should be recalled in non-pro-drop languages (e.g. English). This phenome…
A Simple and Plug-and-play Method for Unsupervised Sentence Representation Enhancement
Lingfeng Shen, Haiyun Jiang, Lemao Liu +1
Generating proper embedding of sentences through an unsupervised way is beneficial to semantic matching and retrieval problems in real-world scenarios. This paper presents Represen…
Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate
Tian Liang, Zhiwei He, Wenxiang Jiao +6
Modern large language models (LLMs) like ChatGPT have shown remarkable performance on general language tasks but still struggle on complex reasoning tasks, which drives the researc…
A Frustratingly Simple Decoding Method for Neural Text Generation
Haoran Yang, Deng Cai, Huayang Li +3
We introduce a frustratingly simple, super efficient and surprisingly effective decoding method, which we call Frustratingly Simple Decoding (FSD), for neural text generation. The…
Exploring Human-Like Translation Strategy with Large Language Models
Zhiwei He, Tian Liang, Wenxiang Jiao +6
Large language models (LLMs) have demonstrated impressive capabilities in general scenarios, exhibiting a level of aptitude that approaches, in some aspects even surpasses, human-l…
ParroT: Translating during Chat using Large Language Models tuned with Human Translation and Feedback
Wenxiang Jiao, Jen-tse Huang, Wenxuan Wang +5
Large language models (LLMs) like ChatGPT have exhibited remarkable abilities on a wide range of natural language processing~(NLP) tasks, including various machine translation abil…
Document-Level Machine Translation with Large Language Models
Longyue Wang, Chenyang Lyu, Tianbo Ji +4
Large language models (LLMs) such as ChatGPT can produce coherent, cohesive, relevant, and fluent answers for various natural language processing (NLP) tasks. Taking document-level…
Is ChatGPT A Good Keyphrase Generator? A Preliminary Study
Mingyang Song, Haiyun Jiang, Shuming Shi +5
The emergence of ChatGPT has recently garnered significant attention from the computational linguistics community. To demonstrate its capabilities as a keyphrase generator, we cond…
Zero-Shot Rumor Detection with Propagation Structure via Prompt Learning
Hongzhan Lin, Pengyao Yi, Jing Ma +4
The spread of rumors along with breaking events seriously hinders the truth in the era of social media. Previous studies reveal that due to the lack of annotated resources, rumors…
Towards Efficient Dialogue Pre-training with Transferable and Interpretable Latent Structure
Xueliang Zhao, Lemao Liu, Tingchen Fu +3
With the availability of massive general-domain dialogue data, pre-trained dialogue generation appears to be super appealing to transfer knowledge from the general domain to downst…