25 citations · 89 across the 17 of their papers we have counts for
18 papers
IntentGrasp: A Comprehensive Benchmark for Intent Understanding
Yuwei Yin, Chuyuan Li, Giuseppe Carenini
Accurately understanding the intent behind speech, conversation, and writing is crucial to the development of helpful Large Language Model (LLM) assistants. This paper introduces I…
Infusing Theory of Mind into Socially Intelligent LLM Agents
EunJeong Hwang, Yuwei Yin, Giuseppe Carenini +2
Theory of Mind (ToM)-an understanding of the mental states of others-is a key aspect of human social intelligence, yet, chatbots and LLM-based social agents do not typically integr…
SWI: Speaking with Intent in Large Language Models
Yuwei Yin, EunJeong Hwang, Giuseppe Carenini
Intent, typically clearly formulated and planned, functions as a cognitive framework for communication and problem-solving. This paper introduces the concept of Speaking with Inten…
Improving Language Models with Intentional Analysis
Yuwei Yin, Giuseppe Carenini
Intent, a critical cognitive notion and mental state, is ubiquitous in human communication and problem-solving. Accurately understanding the underlying intent behind questions is i…
UniCoder: Scaling Code Large Language Model via Universal Code
Tao Sun, Linzheng Chai, Jian Yang +6
Intermediate reasoning or acting steps have successfully improved large language models (LLMs) for handling various downstream natural language processing (NLP) tasks. When applyin…
McEval: Massively Multilingual Code Evaluation
Linzheng Chai, Shukai Liu, Jian Yang +15
Code large language models (LLMs) have shown remarkable advances in code understanding, completion, and generation tasks. Programming benchmarks, comprised of a selection of code c…
m3P: Towards Multimodal Multilingual Translation with Multimodal Prompt
Jian Yang, Hongcheng Guo, Yuwei Yin +7
Multilingual translation supports multiple translation directions by projecting all languages in a shared space, but the translation quality is undermined by the difference between…
Red Teaming Visual Language Models
Mukai Li, Lei Li, Yuwei Yin +3
VLMs (Vision-Language Models) extend the capabilities of LLMs (Large Language Models) to accept multimodal inputs. Since it has been verified that LLMs can be induced to generate h…
MT4CrossOIE: Multi-stage Tuning for Cross-lingual Open Information Extraction
Tongliang Li, Zixiang Wang, Linzheng Chai +8
Cross-lingual open information extraction aims to extract structured information from raw text across multiple languages. Previous work uses a shared cross-lingual pre-trained mode…
FinPT: Financial Risk Prediction with Profile Tuning on Pretrained Foundation Models
Yuwei Yin, Yazheng Yang, Jian Yang +1
Financial risk prediction plays a crucial role in the financial sector. Machine learning methods have been widely applied for automatically detecting potential risks and thus savin…
MIT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning
Lei Li, Yuwei Yin, Shicheng Li +9
Instruction tuning has significantly advanced large language models (LLMs) such as ChatGPT, enabling them to align with human instructions across diverse tasks. However, progress i…
TTIDA: Controllable Generative Data Augmentation via Text-to-Text and Text-to-Image Models
Yuwei Yin, Jean Kaddour, Xiang Zhang +4
Data augmentation has been established as an efficacious approach to supplement useful information for low-resource datasets. Traditional augmentation techniques such as noise inje…
HanoiT: Enhancing Context-aware Translation via Selective Context
Jian Yang, Yuwei Yin, Shuming Ma +7
Context-aware neural machine translation aims to use the document-level context to improve translation quality. However, not all words in the context are helpful. The irrelevant or…
GanLM: Encoder-Decoder Pre-training with an Auxiliary Discriminator
Jian Yang, Shuming Ma, Li Dong +7
Pre-trained models have achieved remarkable success in natural language processing (NLP). However, existing pre-training methods underutilize the benefits of language understanding…
CROP: Zero-shot Cross-lingual Named Entity Recognition with Multilingual Labeled Sequence Translation
Jian Yang, Shaohan Huang, Shuming Ma +6
Named entity recognition (NER) suffers from the scarcity of annotated training data, especially for low-resource languages without labeled data. Cross-lingual NER has been proposed…
UM4: Unified Multilingual Multiple Teacher-Student Model for Zero-Resource Neural Machine Translation
Jian Yang, Yuwei Yin, Shuming Ma +5
Most translation tasks among languages belong to the zero-resource translation problem where parallel corpora are unavailable. Multilingual neural machine translation (MNMT) enable…
HLT-MT: High-resource Language-specific Training for Multilingual Neural Machine Translation
Jian Yang, Yuwei Yin, Shuming Ma +3
Multilingual neural machine translation (MNMT) trained in multiple language pairs has attracted considerable attention due to fewer model parameters and lower training costs by sha…
GTrans: Grouping and Fusing Transformer Layers for Neural Machine Translation
Jian Yang, Yuwei Yin, Liqun Yang +5
Transformer structure, stacked by a sequence of encoder and decoder network layers, achieves significant development in neural machine translation. However, vanilla Transformer mai…