Jinan Xu

Infusing Multi-Source Knowledge with Heterogeneous Graph Neural Network for Emotional Conversation Generation

2021 · Proceedings of the AAAI Conference on Artificial Intelligence

The success of emotional conversation systems depends on sufficient perception and appropriate expression of emotions. In a real-world conversation, we firstly instinctively perceive emotions from multi-source information, including the emotion flow of dialogue history, facial …

Target-oriented Fine-tuning for Zero-Resource Named Entity Recognition

2021

Zero-resource named entity recognition (NER) severely suffers from data scarcity in a specific domain or language. Most studies on zero-resource NER transfer knowledge from various data by fine-tuning on different auxiliary tasks. However, how to …

An Iterative Multi-Knowledge Transfer Network for Aspect-Based Sentiment Analysis

2020 · arXiv (Cornell University)

Aspect-based sentiment analysis (ABSA) mainly involves three subtasks: aspect term extraction, opinion term extraction, and aspect-level sentiment classification, which are typically handled in a separate or joint manner. However, previous approaches do not well exploit …

Complex Question Enhanced Transfer Learning for Zero-Shot Joint Information Extraction

2023 · IEEE/ACM Transactions on Audio Speech and Language Processing

Zero-shot information extraction (IE) tasks have attracted great attention recently. However, how to jointly model multiple IE tasks in the zero-shot scenario is still an open question. In this article, we focus on zero-shot joint …

MT2: Towards a Multi-Task Machine Translation Model with Translation-Specific In-Context Learning

2023

Sentence-level translation, document-level translation, translation memory, and terminology constrained translation play an important role in machine translation. Most of the previous work uses separate models or methods to solve these tasks, which is not conducive …

An Ensemble Strategy with Gradient Conflict for Multi-Domain Neural Machine Translation

2023 · ACM Transactions on Asian and Low-Resource Language Information Processing

Multi-domain neural machine translation aims to construct a unified neural machine translation model to translate sentences across various domains. Nevertheless, previous studies have one limitation is the incapacity to acquire both domain-general and domain-specific representations …

TransportationGames: Benchmarking Transportation Knowledge of (Multimodal) Large Language Models

2024 · arXiv (Cornell University)

Large language models (LLMs) and multimodal large language models (MLLMs) have shown excellent general capabilities, even exhibiting adaptability in many professional domains such as law, economics, transportation, and medicine. Currently, many domain-specific benchmarks have been …

LCS: A Language Converter Strategy for Zero-Shot Neural Machine Translation

2024 · arXiv (Cornell University)

Multilingual neural machine translation models generally distinguish translation directions by the language tag (LT) in front of the source or target sentences. However, current LT strategies cannot indicate the desired target language as expected on …

Evaluation and Benchmarking the Agent Marketing Dialogue Scenarios with Large Language Models

2025

In natural language processing, abilities like text comprehension, reasoning, and generation, which are usually possessed by humans, can often measure the intelligence of an artificial intelligence (AI) model. To a certain extent, measuring the model's …

CM-Align: Consistency-based Multilingual Alignment for Large Language Models

2025 · arXiv (Cornell University)

Current large language models (LLMs) generally show a significant performance gap in alignment between English and other languages. To bridge this gap, existing research typically leverages the model's responses in English as a reference to …

GCDT: A Global Context Enhanced Deep Transition Architecture for Sequence Labeling

2019

Current state-of-the-art systems for the sequence labeling tasks are typically based on the family of Recurrent Neural Networks (RNNs). However, the shallow connections between consecutive hidden states of RNNs and insufficient modeling of global information …

Is ChatGPT a Good NLG Evaluator? A Preliminary Study

2023

Recently, the emergence of ChatGPT has attracted wide attention from the computational linguistics community. Many prior studies have shown that ChatGPT achieves remarkable performance on various NLP tasks in terms of automatic evaluation metrics. However, …