29 citations · 79 across the 20 of their papers we have counts for
20 papers
Evaluating LLM-based Agents for Multi-Turn Conversations: A Survey
Shengyue Guan, Jindong Wang, Jiang Bian +3
This survey examines evaluation methods for large language model (LLM)-based agents in multi-turn conversational settings. Using a PRISMA-inspired framework, we systematically revi…
Pre-trained Molecular Language Models with Random Functional Group Masking
Tianhao Peng, Yuchen Li, Xuhong Li +7
Recent advancements in computational chemistry have leveraged the power of trans-former-based language models, such as MoLFormer, pre-trained using a vast amount of simplified mole…
Generative Pre-trained Ranking Model with Over-parameterization at Web-Scale (Extended Abstract)
Yuchen Li, Haoyi Xiong, Linghe Kong +4
Learning to rank (LTR) is widely employed in web searches to prioritize pertinent webpages from retrieved content based on input queries. However, traditional LTR models encounter…
Towards Automated Data Sciences with Natural Language and SageCopilot: Practices and Lessons Learned
Yuan Liao, Jiang Bian, Yuhui Yun +9
While the field of NL2SQL has made significant advancements in translating natural language instructions into executable SQL scripts for data querying and processing, achieving ful…
Converging Paradigms: The Synergy of Symbolic and Connectionist AI in LLM-Empowered Autonomous Agents
Haoyi Xiong, Zhiyuan Wang, Xuhong Li +5
This article explores the convergence of connectionist and symbolic artificial intelligence (AI), from historical debates to contemporary advancements. Traditionally considered dis…
When Search Engine Services meet Large Language Models: Visions and Challenges
Haoyi Xiong, Jiang Bian, Yuchen Li +5
Combining Large Language Models (LLMs) with search engine services marks a significant shift in the field of services computing, opening up new possibilities to enhance how we sear…
TiC: Exploring Vision Transformer in Convolution
Song Zhang, Qingzhong Wang, Jiang Bian +1
While models derived from Vision Transformers (ViTs) have been phonemically surging, pre-trained models cannot seamlessly adapt to arbitrary resolution images without altering the…
Natural Language based Context Modeling and Reasoning for Ubiquitous Computing with Large Language Models: A Tutorial
Haoyi Xiong, Jiang Bian, Sijia Yang +3
Large language models (LLMs) have become phenomenally surging, since 2018--two decades after introducing context-awareness into computing systems. Through taking into account the s…
Video4MRI: An Empirical Study on Brain Magnetic Resonance Image Analytics with CNN-based Video Classification Frameworks
Yuxuan Zhang, Qingzhong Wang, Jiang Bian +4
To address the problem of medical image recognition, computer vision techniques like convolutional neural networks (CNN) are frequently used. Recently, 3D CNN-based models dominate…
Learning from Training Dynamics: Identifying Mislabeled Data Beyond Manually Designed Features
Qingrui Jia, Xuhong Li, Lei Yu +5
While mislabeled or ambiguously-labeled samples in the training set could negatively affect the performance of deep models, diagnosing the dataset and identifying mislabeled sample…
GLARE: A Dataset for Traffic Sign Detection in Sun Glare
Nicholas Gray, Megan Moraes, Jiang Bian +6
Real-time machine learning object detection algorithms are often found within autonomous vehicle technology and depend on quality datasets. It is essential that these algorithms wo…
AA-Forecast: Anomaly-Aware Forecast for Extreme Events
Ashkan Farhangi, Jiang Bian, Arthur Huang +3
Time series models often deal with extreme events and anomalies, both prevalent in real-world datasets. Such models often need to provide careful probabilistic forecasting, which i…
P2ANet: A Dataset and Benchmark for Dense Action Detection from Table Tennis Match Broadcasting Videos
Jiang Bian, Xuhong Li, Tao Wang +7
While deep learning has been widely used for video analytics, such as video classification and action detection, dense action detection with fast-moving subjects from sports videos…
A Survey on Video Action Recognition in Sports: Datasets, Methods and Applications
Fei Wu, Qingzhong Wang, Jian Bian +5
To understand human behaviors, action recognition based on videos is a common approach. Compared with image-based action recognition, videos provide much more information. Reducing…
A Simple yet Effective Framework for Active Learning to Rank
Qingzhong Wang, Haifang Li, Haoyi Xiong +7
While China has become the biggest online market in the world with around 1 billion internet users, Baidu runs the world largest Chinese search engine serving more than hundreds of…
MoESys: A Distributed and Efficient Mixture-of-Experts Training and Inference System for Internet Services
Dianhai Yu, Liang Shen, Hongxiang Hao +5
While modern internet services, such as chatbots, search engines, and online advertising, demand the use of large-scale deep neural networks (DNNs), distributed training and infere…
Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and Beyond
Xuhong Li, Haoyi Xiong, Xingjian Li +5
Deep neural networks have been well-known for their superb handling of various machine learning and artificial intelligence tasks. However, due to their over-parameterized black-bo…
CSWA: Aggregation-Free Spatial-Temporal Community Sensing
Jiang Bian, Haoyi Xiong, Yanjie Fu +1
In this paper, we present a novel community sensing paradigm -- {C}ommunity {S}ensing {W}ithout {A}ggregation}. CSWA is designed to obtain the environment information (e.g., air po…
FWDA: a Fast Wishart Discriminant Analysis with its Application to Electronic Health Records Data Classification
Haoyi Xiong, Wei Cheng, Wenqing Hu +2
Linear Discriminant Analysis (LDA) on Electronic Health Records (EHR) data is widely-used for early detection of diseases. Classical LDA for EHR data classification, however, suffe…
Improving Covariance-Regularized Discriminant Analysis for EHR-based Predictive Analytics of Diseases
Sijia Yang, Haoyi Xiong, Kaibo Xu +3
Linear Discriminant Analysis (LDA) is a well-known technique for feature extraction and dimension reduction. The performance of classical LDA, however, significantly degrades on th…