Xipeng Qiu

Gated Recursive Neural Network for Chinese Word Segmentation

2015

Xinchi Chen, Xipeng Qiu, Chenxi Zhu, Xuanjing Huang. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 2015.

Learning Sparse Sharing Architectures for Multiple Tasks

2020 · Proceedings of the AAAI Conference on Artificial Intelligence

Most existing deep multi-task learning models are based on parameter sharing, such as hard sharing, hierarchical sharing, and soft sharing. How choosing a suitable sharing mechanism depends on the relations among the tasks, which is …

A Unified Generative Framework for Aspect-Based Sentiment Analysis

2021 · arXiv (Cornell University)

Aspect-based Sentiment Analysis (ABSA) aims to identify the aspect terms, their corresponding sentiment polarities, and the opinion terms. There exist seven subtasks in ABSA. Most studies only focus on the subsets of these subtasks, which …

SeqXGPT: Sentence-Level AI-Generated Text Detection

2023

Widely applied large language models (LLMs) can generate human-like content, raising concerns about the abuse of LLMs. Therefore, it is important to build strong AI-generated text (AIGT) detectors. Current works only consider document-level AIGT detection, …

Plan, Verify and Switch: Integrated Reasoning with Diverse X-of-Thoughts

2023

As large language models (LLMs) have shown effectiveness with different prompting methods, such as Chain of Thought, Program of Thought, we find that these methods have formed a great complementarity to each other on math …

SpeechGPT-Gen: Scaling Chain-of-Information Speech Generation

2024 · arXiv (Cornell University)

Benefiting from effective speech modeling, current Speech Large Language Models (SLLMs) have demonstrated exceptional capabilities in in-context speech generation and efficient generalization to unseen speakers. However, the prevailing information modeling process is encumbered by certain …

MCM-DPO: Multifaceted Cross-Modal Direct Preference Optimization for Alt-text Generation

2025 · arXiv (Cornell University)

The alt-text generation task produces concise, context-relevant descriptions of images, enabling blind and low-vision users to access online images. Despite the capabilities of large vision-language models, alt-text generation performance remains limited due to noisy user …

Reinforced Interactive Continual Learning via Real-time Noisy Human Feedback

2025 · arXiv (Cornell University)

This paper introduces an interactive continual learning paradigm where AI models dynamically learn new skills from real-time human feedback while retaining prior knowledge. This paradigm distinctively addresses two major limitations of traditional continual learning: (1) …

Pre-Trained Policy Discriminators are General Reward Models

2025

We offer a novel perspective on reward modeling by formulating it as a policy discriminator, which quantifies the difference between two policies to generate a reward signal, guiding the training policy towards a target policy …

Long Short-Term Memory Neural Networks for Chinese Word Segmentation

2015

Currently most of state-of-the-art methods for Chinese word segmentation are based on supervised learning, whose features are mostly extracted from a local context.These methods cannot utilize the long distance information which is also crucial for …

Multi-Timescale Long Short-Term Memory Neural Network for Modelling Sentences and Documents

2015

Neural network based methods have obtained great progress on a variety of natural language processing tasks. However, it is still a challenge task to model long texts, such as sentences and documents. In this paper, …

Convolutional neural tensor network architecture for community-based question answering

2015 · International Conference on Artificial Intelligence

Retrieving similar questions is very important in community-based question answering. A major challenge is the lexical gap in sentence matching. In this paper, we propose a convolutional neural tensor network architecture to encode the sentences …

Recurrent Neural Network for Text Classification with Multi-Task Learning

2016 · arXiv (Cornell University)

Neural network based methods have obtained great progress on a variety of natural language processing tasks. However, in most previous works, the models are learned based on single-task supervised objectives, which often suffer from insufficient …

Style Transformer: Unpaired Text Style Transfer without Disentangled Latent Representation

2019

Disentangling the content and style in the latent space is prevalent in unpaired text style transfer. However, two major issues exist in most of the current neural models. 1) It is difficult to completely strip …

Utilizing

2019

Chi Sun, Luyao Huang, Xipeng Qiu. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.

Adversarial Multi-task Learning for Text Classification

2017

Neural network models have shown their promising opportunities for multi-task learning, which focus on learning the shared layers to extract the common and task-invariant features. However, in most existing approaches, the extracted shared features are …

Adversarial Multi-Criteria Learning for Chinese Word Segmentation

2017

Different linguistic perspectives causes many diverse segmentation criteria for Chinese word segmentation (CWS). Most existing methods focus on improve the performance for each single criterion. However, it is interesting to exploit these different criteria and …

Searching for Effective Neural Extractive Summarization: What Works and What’s Next

2019

The recent years have seen remarkable success in the use of deep neural networks on text summarization. However, there is no clear understanding of why they perform so well, or how they might be improved. …

GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge

2019

Luyao Huang, Chi Sun, Xipeng Qiu, Xuanjing Huang. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019.

TENER: Adapting Transformer Encoder for Named Entity Recognition

2019 · arXiv (Cornell University)

The Bidirectional long short-term memory networks (BiLSTM) have been widely used as an encoder in models solving the named entity recognition (NER) task. Recently, the Transformer is broadly adopted in various Natural Language Processing (NLP) …

Heterogeneous Graph Neural Networks for Extractive Document Summarization

2020

As a crucial step in extractive document summarization, learning cross-sentence relations has been explored by a plethora of approaches. An intuitive way is to put them in the graphbased neural network, which has a more …

FLAT: Chinese NER Using Flat-Lattice Transformer

2020

Recently, the character-word lattice structure has been proved to be effective for Chinese named entity recognition (NER) by incorporating the word information. However, since the lattice structure is complex and dynamic, most existing lattice-based models …

Extractive Summarization as Text Matching

2020

This paper creates a paradigm shift with regard to the way we build neural extractive summarization systems. Instead of following the commonly used framework of extracting sentences individually and modeling the relationship between sentences, we …

QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization

2021

Ming Zhong, Da Yin, Tao Yu, Ahmad Zaidi, Mutethia Mutuma, Rahul Jha, Ahmed Hassan Awadallah, Asli Celikyilmaz, Yang Liu, Xipeng Qiu, Dragomir Radev. Proceedings of the 2021 Conference of the North American Chapter of the …