Qian Liu

Digital media recommendation system design based on user behavior analysis and emotional feature extraction

2025 · PLoS ONE

In the contemporary digital era, multimedia platforms, such as social media, online comment sections, and forums, have emerged as the primary arenas wherein users articulate their sentiments and viewpoints. The copious volume of textual data …

Learning Algebraic Recombination for Compositional Generalization

2021 · arXiv (Cornell University)

Neural sequence models exhibit limited compositional generalization ability in semantic parsing tasks. Compositional generalization requires algebraic recombination, i.e., dynamically recombining structured expressions in a recursive manner. However, most previous studies mainly concentrate on recombining lexical …

Disentangled Retrieval and Reasoning for Implicit Question Answering

2022 · IEEE Transactions on Neural Networks and Learning Systems

To date, most of the existing open-domain question answering (QA) methods focus on explicit questions where the reasoning steps are mentioned explicitly in the question. In this article, we study implicit QA where the reasoning …

Bag of Tricks for Training Data Extraction from Language Models

2023 · arXiv (Cornell University)

With the advance of language models, privacy protection is receiving more attention. Training data extraction is therefore of great importance, as it can serve as a potential tool to assess privacy leakage. However, due to …

Patch-based deep learning models for breast mammographic mass classification

2023

Background: Breast cancer is one of the greatest health threats to women worldwide. Mammography is an effective and inexpensive tool for breast cancer early detection. Mammography-based breast cancer screening requires a lot of manpower from …

New Cryptographic Bent Functions from Permutations and Linear Translator in Cyber Security

2023

Cryptographic bent functions are maximally nonlinear Boolean functions with an even number of variables. They are not only closely related to some interesting combinatorial objects, but also have important applications in coding, sequence design, cryptography …

Designing an Efficient Framework for Large-Scale Data Processing and Analysis Based on Deep Learning Technology

2024

This paper presents a comprehensive framework designed for the efficient processing and analysis of large-scale data through the integration of deep learning technologies. The framework leverages the capabilities of deep learning to enhance the accuracy …

Beyond Memorization: The Challenge of Random Memory Access in Language Models

2024

Recent developments in Language Models (LMs) have shown their effectiveness in NLP tasks, particularly in knowledge-intensive tasks.However, the mechanisms underlying knowledge storage and memory access within their parameters remain elusive.In this paper, we investigate whether …

PanoSent: A Panoptic Sextuple Extraction Benchmark for Multimodal Conversational Aspect-based Sentiment Analysis

2024 · arXiv (Cornell University)

While existing Aspect-based Sentiment Analysis (ABSA) has received extensive effort and advancement, there are still gaps in defining a more holistic research target seamlessly integrating multimodality, conversation context, fine-granularity, and also covering the changing sentiment …

An Adaptive Framework for Temporal Knowledge Graph Reasoning with Dynamic Event-Driven Dependencies

2024

Temporal knowledge graph reasoning plays an important role in dynamic systems, event prediction, and complex temporal analysis. However, existing reasoning methods often struggle with challenges such as long-term temporal dependencies, data sparsity, and burst events. …

Active Retrieval Augmented Generation

2023

Zhengbao Jiang, Frank Xu, Luyu Gao, Zhiqing Sun, Qian Liu, Jane Dwivedi-Yu, Yiming Yang, Jamie Callan, Graham Neubig. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. 2023.