Search Results - "Lu, Keming"

Multi‐Task Learning for Simultaneous Retrievals of Passive Microwave Precipitation Estimates and Rain/No‐Rain Classification by Bannai, Takumi, Xu, Haoyang, Utsumi, Nobuyuki, Koo, Eunho, Lu, Keming, Kim, Hyungjun

“…Satellite‐based precipitation estimations provide frequent, large‐scale measurements. Deep learning has recently shown significant potential for improving…”
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Can natural language processing help differentiate inflammatory intestinal diseases in China? Models applying random forest and convolutional neural network approaches by Tong, Yuanren, Lu, Keming, Yang, Yingyun, Li, Ji, Lin, Yucong, Wu, Dong, Yang, Aiming, Li, Yue, Yu, Sheng, Qian, Jiaming

“…Differentiating between ulcerative colitis (UC), Crohn's disease (CD) and intestinal tuberculosis (ITB) using endoscopy is challenging. We aimed to realize…”
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Building a trustworthy AI differential diagnosis application for Crohn’s disease and intestinal tuberculosis by Lu, Keming, Tong, Yuanren, Yu, Si, Lin, Yucong, Yang, Yingyun, Xu, Hui, Li, Yue, Yu, Sheng

“…Abstract Background Differentiating between Crohn’s disease (CD) and intestinal tuberculosis (ITB) with endoscopy is challenging. We aim to perform more…”
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The Role of In-Group and Out-Group Facial Feedback in Implicit Rule Learning by Ou, Meijun, Peng, Wenjie, Zhang, Wenyang, Ouyang, Muxin, Liu, Yiling, Lu, Keming, Zeng, Xiangyan, Yuan, Jie

“…Implicit learning refers to the fact that people acquire new knowledge (structures or rules) without conscious awareness. Previous studies have shown that…”
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By Carrot or by Stick: The Influence of Encouraging and Discouraging Facial Feedback on Implicit Rule Learning by Liu, Yiling, Ouyang, Muxin, Peng, Wenjie, Zhang, Wenyang, Lu, Keming, He, Yujun, Zeng, Xiangyan, Yuan, Jie

“…Implicit learning refers to the process of unconsciously learning complex knowledge through feedback. Previous studies investigated the influences of different…”
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Multimodal learning on graphs for disease relation extraction by Lin, Yucong, Lu, Keming, Yu, Sheng, Cai, Tianxi, Zitnik, Marinka

“…Disease knowledge graphs have emerged as a powerful tool for artificial intelligence to connect, organize, and access diverse information about diseases…”
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Long-distance disorder-disorder relation extraction with bootstrapped noisy data by Lin, Yucong, Li, Yang, Lu, Keming, Ma, Cheng, Zhao, Peng, Gao, Daiqi, Fan, Zihao, Cheng, Zijie, Wang, Zheyu, Yu, Sheng

“…[Display omitted] •Accurate relation extraction algorithms can be developed without manual annotation.•Relaxing the assumption on the sentence form resulted in…”
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Expectation-maximization algorithms, null spaces, and MAP image restoration by Hebert, T.J., Keming Lu

“…A computationally efficient, easily implementable algorithm for MAP restoration of images degraded by blur and additive correlated Gaussian noise using Gibbs…”
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Image reconstruction for electrical impedance tomography based on spatial invariant feature maps and convolutional neural network by Hu, Delin, Lu, Keming, Yang, Yunjie

“…Data-driven methods are attracting more and more attention in the field of electrical impedance tomography. Many learning-based tomographic algorithms have…”
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Exploring Partial Knowledge Base Inference in Biomedical Entity Linking by Yuan, Hongyi, Lu, Keming, Yuan, Zheng

“…Biomedical entity linking (EL) consists of named entity recognition (NER) and named entity disambiguation (NED). EL models are trained on corpora labeled by a…”
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Large Language Models are Superpositions of All Characters: Attaining Arbitrary Role-play via Self-Alignment by Lu, Keming, Yu, Bowen, Zhou, Chang, Zhou, Jingren

“…Considerable efforts have been invested in augmenting the role-playing proficiency of open-source large language models (LLMs) by emulating proprietary…”
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Speculative Contrastive Decoding by Yuan, Hongyi, Lu, Keming, Huang, Fei, Yuan, Zheng, Zhou, Chang

“…Large language models~(LLMs) exhibit exceptional performance in language tasks, yet their auto-regressive inference is limited due to high computational…”
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A Unified View of Delta Parameter Editing in Post-Trained Large-Scale Models by Tang, Qiaoyu, Yu, Le, Yu, Bowen, Lin, Hongyu, Lu, Keming, Lu, Yaojie, Han, Xianpei, Sun, Le

“…Post-training has emerged as a crucial paradigm for adapting large-scale pre-trained models to various tasks, whose effects are fully reflected by delta…”
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Predicting Rewards Alongside Tokens: Non-disruptive Parameter Insertion for Efficient Inference Intervention in Large Language Model by Yuan, Chenhan, Huang, Fei, Peng, Ru, Lu, Keming, Yu, Bowen, Zhou, Chang, Zhou, Jingren

“…Transformer-based large language models (LLMs) exhibit limitations such as generating unsafe responses, unreliable reasoning, etc. Existing inference…”
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Self-play with Execution Feedback: Improving Instruction-following Capabilities of Large Language Models by Dong, Guanting, Lu, Keming, Li, Chengpeng, Xia, Tingyu, Yu, Bowen, Zhou, Chang, Zhou, Jingren

“…One core capability of large language models (LLMs) is to follow natural language instructions. However, the issue of automatically constructing high-quality…”
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Online Merging Optimizers for Boosting Rewards and Mitigating Tax in Alignment by Lu, Keming, Yu, Bowen, Huang, Fei, Fan, Yang, Lin, Runji, Zhou, Chang

“…Effectively aligning Large Language Models (LLMs) with human-centric values while preventing the degradation of abilities acquired through Pre-training and…”
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Aligning Large Language Models via Self-Steering Optimization by Xiang, Hao, Yu, Bowen, Lin, Hongyu, Lu, Keming, Lu, Yaojie, Han, Xianpei, Sun, Le, Zhou, Jingren, Lin, Junyang

“…Automated alignment develops alignment systems with minimal human intervention. The key to automated alignment lies in providing learnable and accurate…”
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Multimodal Learning on Graphs for Disease Relation Extraction by Lin, Yucong, Lu, Keming, Yu, Sheng, Cai, Tianxi, Zitnik, Marinka

“…Objective: Disease knowledge graphs are a way to connect, organize, and access disparate information about diseases with numerous benefits for artificial…”
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Routing to the Expert: Efficient Reward-guided Ensemble of Large Language Models by Lu, Keming, Yuan, Hongyi, Lin, Runji, Lin, Junyang, Yuan, Zheng, Zhou, Chang, Zhou, Jingren

“…The complementary potential of Large Language Models (LLM) assumes off-the-shelf LLMs have heterogeneous expertise in a wide range of domains and tasks so that…”
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Self-Evolved Diverse Data Sampling for Efficient Instruction Tuning by Wu, Shengguang, Lu, Keming, Xu, Benfeng, Lin, Junyang, Su, Qi, Zhou, Chang

“…Enhancing the instruction-following ability of Large Language Models (LLMs) primarily demands substantial instruction-tuning datasets. However, the sheer…”
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