Search Results for author: Chen Ling

Found 26 papers, 10 papers with code

Gradient-Free Adaptive Global Pruning for Pre-trained Language Models

1 code implementation28 Feb 2024 Guangji Bai, Yijiang Li, Chen Ling, Kibaek Kim, Liang Zhao

The transformative impact of large language models (LLMs) like LLaMA and GPT on natural language processing is countered by their prohibitive computational demands.

Computational Efficiency Problem Decomposition

MIM-Reasoner: Learning with Theoretical Guarantees for Multiplex Influence Maximization

1 code implementation24 Feb 2024 Nguyen Do, Tanmoy Chowdhury, Chen Ling, Liang Zhao, My T. Thai

Multiplex influence maximization (MIM) asks us to identify a set of seed users such as to maximize the expected number of influenced users in a multiplex network.

ELAD: Explanation-Guided Large Language Models Active Distillation

no code implementations20 Feb 2024 Yifei Zhang, Bo Pan, Chen Ling, Yuntong Hu, Liang Zhao

The deployment and application of Large Language Models (LLMs) is hindered by their memory inefficiency, computational demands, and the high costs of API inferences.

Active Learning Knowledge Distillation

A Condensed Transition Graph Framework for Zero-shot Link Prediction with Large Language Models

no code implementations16 Feb 2024 Mingchen Li, Chen Ling, Rui Zhang, Liang Zhao

To address this, in this work, we introduce a Condensed Transition Graph Framework for Zero-Shot Link Prediction (CTLP), which encodes all the paths' information in linear time complexity to predict unseen relations between entities, attaining both efficiency and information preservation.

Contrastive Learning Knowledge Graphs +1

Uncertainty Quantification for In-Context Learning of Large Language Models

1 code implementation15 Feb 2024 Chen Ling, Xujiang Zhao, Xuchao Zhang, Wei Cheng, Yanchi Liu, Yiyou Sun, Mika Oishi, Takao Osaki, Katsushi Matsuda, Jie Ji, Guangji Bai, Liang Zhao, Haifeng Chen

Existing works have been devoted to quantifying the uncertainty in LLM's response, but they often overlook the complex nature of LLMs and the uniqueness of in-context learning.

Hallucination In-Context Learning +1

Gene-associated Disease Discovery Powered by Large Language Models

no code implementations16 Jan 2024 Jiayu Chang, Shiyu Wang, Chen Ling, Zhaohui Qin, Liang Zhao

The intricate relationship between genetic variation and human diseases has been a focal point of medical research, evidenced by the identification of risk genes regarding specific diseases.

Decision Making Retrieval

Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models

1 code implementation1 Jan 2024 Guangji Bai, Zheng Chai, Chen Ling, Shiyu Wang, Jiaying Lu, Nan Zhang, Tingwei Shi, Ziyang Yu, Mengdan Zhu, Yifei Zhang, Carl Yang, Yue Cheng, Liang Zhao

We categorize methods based on their optimization focus: computational, memory, energy, financial, and network resources and their applicability across various stages of an LLM's lifecycle, including architecture design, pretraining, finetuning, and system design.

Open-ended Commonsense Reasoning with Unrestricted Answer Scope

no code implementations18 Oct 2023 Chen Ling, Xuchao Zhang, Xujiang Zhao, Yanchi Liu, Wei Cheng, Mika Oishi, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao

In this work, we leverage pre-trained language models to iteratively retrieve reasoning paths on the external knowledge base, which does not require task-specific supervision.

Question Answering Retrieval

Helper Recommendation with seniority control in Online Health Community

no code implementations6 Sep 2023 Junruo Gao, Chen Ling, Carl Yang, Liang Zhao

Online health communities (OHCs) are forums where patients with similar conditions communicate their experiences and provide moral support.

Recommendation Systems

Deep Graph Representation Learning and Optimization for Influence Maximization

1 code implementation1 May 2023 Chen Ling, Junji Jiang, Junxiang Wang, My Thai, Lukas Xue, James Song, Meikang Qiu, Liang Zhao

Influence maximization (IM) is formulated as selecting a set of initial users from a social network to maximize the expected number of influenced users.

Graph Representation Learning

Knowledge-enhanced Neural Machine Reasoning: A Review

no code implementations4 Feb 2023 Tanmoy Chowdhury, Chen Ling, Xuchao Zhang, Xujiang Zhao, Guangji Bai, Jian Pei, Haifeng Chen, Liang Zhao

Knowledge-enhanced neural machine reasoning has garnered significant attention as a cutting-edge yet challenging research area with numerous practical applications.

Saliency-Augmented Memory Completion for Continual Learning

1 code implementation26 Dec 2022 Guangji Bai, Chen Ling, Yuyang Gao, Liang Zhao

Specifically, we innovatively propose to store the part of the image most important to the tasks in episodic memory by saliency map extraction and memory encoding.

Bilevel Optimization Continual Learning +1

DeepGAR: Deep Graph Learning for Analogical Reasoning

1 code implementation19 Nov 2022 Chen Ling, Tanmoy Chowdhury, Junji Jiang, Junxiang Wang, Xuchao Zhang, Haifeng Chen, Liang Zhao

As the most well-known computational method of analogical reasoning, Structure-Mapping Theory (SMT) abstracts both target and base subjects into relational graphs and forms the cognitive process of analogical reasoning by finding a corresponding subgraph (i. e., correspondence) in the target graph that is aligned with the base graph.

Graph Learning

Source Localization of Graph Diffusion via Variational Autoencoders for Graph Inverse Problems

1 code implementation24 Jun 2022 Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao

Different from most traditional source localization methods, this paper focuses on a probabilistic manner to account for the uncertainty of different candidate sources.

Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks

1 code implementation21 May 2022 Guangji Bai, Chen Ling, Liang Zhao

Temporal domain generalization is a promising yet extremely challenging area where the goal is to learn models under temporally changing data distributions and generalize to unseen data distributions following the trends of the change.

Domain Generalization Graph Generation

Slapping Cats, Bopping Heads, and Oreo Shakes: Understanding Indicators of Virality in TikTok Short Videos

no code implementations3 Nov 2021 Chen Ling, Jeremy Blackburn, Emiliano De Cristofaro, Gianluca Stringhini

We do so vis-\`a-vis three research hypotheses; namely, that: 1) the video content, 2) TikTok's recommendation algorithm, and 3) the popularity of the video creator contribute to virality.

Cultural Vocal Bursts Intensity Prediction

"Sparse + Low-Rank'' Tensor Completion Approach for Recovering Images and Videos

no code implementations18 Oct 2021 Chenjian Pan, Chen Ling, Hongjin He, Liqun Qi, Yanwei Xu

By the multi-dimensional nature of color images and videos, in this paper, we propose a novel tensor completion approach, which is able to efficiently explore the sparsity of tensor data under the discrete cosine transform (DCT).

Face Recognition Image Inpainting

Low-Rank and Sparse Enhanced Tucker Decomposition for Tensor Completion

no code implementations1 Oct 2020 Chenjian Pan, Chen Ling, Hongjin He, Liqun Qi, Yanwei Xu

Our model possesses a sparse regularization term to promote a sparse core tensor of the Tucker decomposition, which is beneficial for tensor data compression.

Data Compression Face Recognition

"Go eat a bat, Chang!": On the Emergence of Sinophobic Behavior on Web Communities in the Face of COVID-19

no code implementations8 Apr 2020 Fatemeh Tahmasbi, Leonard Schild, Chen Ling, Jeremy Blackburn, Gianluca Stringhini, Yang Zhang, Savvas Zannettou

Finally, we find interesting differences in the context in which words related to Chinese people are used on the Web before and after the COVID-19 outbreak: on Twitter we observe a shift towards blaming China for the situation, while on /pol/ we find a shift towards using more (and new) Sinophobic slurs.

Word Embeddings Social and Information Networks Computers and Society

SocialGrid: A TCN-enhanced Method for Online Discussion Forecasting

1 code implementation16 Mar 2020 Chen Ling, Ruiqi Wang, Guangmo Tong

Based on the nature of the grid, we leverage the Temporal Convolution Network to learn the dynamics at the grid level.

Social and Information Networks

NesTPP: Modeling Thread Dynamics in Online Discussion Forums

no code implementations12 Mar 2020 Chen Ling, Guangmo Tong, Mozi Chen

Online discussion forum creates an asynchronous conversation environment for online users to exchange ideas and share opinions through a unique thread-reply communication mode.

Social and Information Networks

Time-constrained Adaptive Influence Maximization

no code implementations6 Jan 2020 Guangmo Tong, Ruiqi Wang, Chen Ling, Zheng Dong, Xiang Li

The well-known influence maximization problem aims at maximizing the influence of one information cascade in a social network by selecting appropriate seed users prior to the diffusion process.

Social and Information Networks

Geo-SAGE: A Geographical Sparse Additive Generative Model for Spatial Item Recommendation

no code implementations12 Mar 2015 Wang Weiqing, Yin Hongzhi, Chen Ling, Sun Yizhou, Sadiq Shazia, Zhou Xiaofang

Geo-SAGE considers both user personal interests and the preference of the crowd in the target region, by exploiting both the co-occurrence pattern of spatial items and the content of spatial items.

Recommendation Systems

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