1 code implementation • 15 Jan 2025 • Han Wang, Jianqiang Li, Qing Zhao, Zhonglong Chen, Changwei Song, Jing Tang, Yuning Huang, Wei Zhai, Yongsheng Tong, Guanghui Fu
Mental health is a critical global public health issue, and psychological support hotlines play a pivotal role in providing mental health assistance and identifying suicide risks at an early stage.
no code implementations • 30 Dec 2024 • Xingjian Tao, Yiwei Wang, Yujun Cai, Zhicheng Yang, Jing Tang
Large language models (LLMs) have shown promise as potential knowledge bases, yet they often struggle with question-answering tasks and are prone to hallucinations.
1 code implementation • 8 Dec 2024 • Fan Wang, Juyong Jiang, Chansung Park, Sunghun Kim, Jing Tang
The increasing sizes of large language models (LLMs) result in significant computational overhead and memory usage when adapting these models to specific tasks or domains.
no code implementations • 22 Nov 2024 • Atilla P. Kiraly, Sebastien Baur, Kenneth Philbrick, Fereshteh Mahvar, Liron Yatziv, Tiffany Chen, Bram Sterling, Nick George, Fayaz Jamil, Jing Tang, Kai Bailey, Faruk Ahmed, Akshay Goel, Abbi Ward, Lin Yang, Andrew Sellergren, Yossi Matias, Avinatan Hassidim, Shravya Shetty, Daniel Golden, Shekoofeh Azizi, David F. Steiner, Yun Liu, Tim Thelin, Rory Pilgrim, Can Kirmizibayrak
Finally, while HAI-DEF and specifically the foundation models lower the barrier to entry for ML in healthcare, we emphasize the importance of validation with problem- and population-specific data for each desired usage setting.
1 code implementation • 24 Oct 2024 • Qifan Zhang, Xiaobin Hong, Jianheng Tang, Nuo Chen, Yuhan Li, Wenzhong Li, Jing Tang, Jia Li
Furthermore, GCoder efficiently manages large-scale graphs with millions of nodes and diverse input formats, overcoming the limitations of previous models focused on the reasoning steps paradigm.
no code implementations • 23 Oct 2024 • Tianyuan Jin, Keke Huang, Jing Tang, Xiaokui Xiao
We propose an algorithm that works for any $k$ and achieves the optimal sample complexity $O(\frac{n}{\eps^2} \log\frac{k}{\delta})$ using a single-arm memory and a single pass of the stream.
1 code implementation • 22 Oct 2024 • Yihong Luo, Yuhan Chen, Siya Qiu, Yiwei Wang, Chen Zhang, Yan Zhou, Xiaochun Cao, Jing Tang
The standard SAM approach, however, consists of two forward-backward steps in each training iteration, doubling the computational cost compared to the base optimizer (e. g., Adam).
no code implementations • 3 Oct 2024 • Mayank Daswani, Mathias M. J. Bellaiche, Marc Wilson, Desislav Ivanov, Mikhail Papkov, Eva Schnider, Jing Tang, Kay Lamerigts, Gabriela Botea, Michael A. Sanchez, Yojan Patel, Shruthi Prabhakara, Shravya Shetty, Umesh Telang
While multimodal foundation models can now natively work with data beyond text, they remain underutilized in analyzing the considerable amounts of multi-dimensional time-series data in fields like healthcare, finance, and social sciences, representing a missed opportunity for richer, data-driven insights.
1 code implementation • 24 Aug 2024 • Chansung Park, Juyong Jiang, Fan Wang, Sayak Paul, Jing Tang
The widespread adoption of cloud-based proprietary large language models (LLMs) has introduced significant challenges, including operational dependencies, privacy concerns, and the necessity of continuous internet connectivity.
no code implementations • 23 Aug 2024 • Yafeng Zhang, Zilan Yu, Yuang Huang, Jing Tang
To address this issue, we propose CLLMFS, a Contrastive Learning enhanced Large Language Model (LLM) Framework for Few-Shot Named Entity Recognition, achieving promising results with limited training data.
1 code implementation • 18 Aug 2024 • Jing Tang, Quanlu Jia, Yuqiang Xie, Zeyu Gong, Xiang Wen, Jiayi Zhang, Yalong Guo, Guibin Chen, Jiangping Yang
We perform keyframe extraction and annotation on each episode to obtain about 10, 000, 000 shooting scripts.
1 code implementation • 13 Jul 2024 • Zhicheng Yang, Yiwei Wang, Yinya Huang, Zhijiang Guo, Wei Shi, Xiongwei Han, Liang Feng, Linqi Song, Xiaodan Liang, Jing Tang
Furthermore, to alleviate the data scarcity for optimization problems, and to bridge the gap between open-source LLMs on a small scale (e. g., Llama-3-8b) and closed-source LLMs (e. g., GPT-4), we further propose a data synthesis method namely ReSocratic.
1 code implementation • 9 Jul 2024 • Jiaxi Cui, Wentao Zhang, Jing Tang, Xudong Tong, Zhenwei Zhang, Amie, Jing Wen, Rongsheng Wang, Pengfei Wu
Our findings demonstrate that models fine-tuned using the \textbf{Task-Fine-Tune} methodology not only achieve superior performance on these specific tasks but also significantly outperform models with higher general capabilities in their respective domains.
1 code implementation • 26 Jun 2024 • Weilin Cai, Juyong Jiang, Fan Wang, Jing Tang, Sunghun Kim, Jiayi Huang
Large language models (LLMs) have garnered unprecedented advancements across diverse fields, ranging from natural language processing to computer vision and beyond.
2 code implementations • 4 Jun 2024 • Jianqiao Lu, Yingjia Wan, Zhengying Liu, Yinya Huang, Jing Xiong, Chengwu Liu, Jianhao Shen, Hui Jin, Jipeng Zhang, Haiming Wang, Zhicheng Yang, Jing Tang, Zhijiang Guo
Autoformalization, the conversion of natural language mathematics into formal languages, offers significant potential for advancing mathematical reasoning.
1 code implementation • 23 May 2024 • Haiming Wang, Huajian Xin, Zhengying Liu, Wenda Li, Yinya Huang, Jianqiao Lu, Zhicheng Yang, Jing Tang, Jian Yin, Zhenguo Li, Xiaodan Liang
This approach allows the theorem to be tackled incrementally by outlining the overall theorem at the first level and then solving the intermediate conjectures at deeper levels.
1 code implementation • 19 Mar 2024 • Yihong Luo, Xiaolong Chen, Xinghua Qu, Tianyang Hu, Jing Tang
We show that our method can serve as a one-step generation model training from scratch with competitive performance.
1 code implementation • 23 Dec 2023 • Zhangli Lu, Chuqi Lei, Kaili Wang, Libo Qin, Jing Tang, Min Li
DTIAM, for the first time, provides a unified framework for accurate and robust prediction of drug-target interactions, binding affinities, and activation/inhibition mechanisms.
1 code implementation • 20 Dec 2023 • Jiaxi Cui, Liuzhenghao Lv, Jing Wen, Rongsheng Wang, Jing Tang, Yonghong Tian, Li Yuan
We present a novel approach for integrating Myers-Briggs Type Indicator (MBTI) personality traits into large language models (LLMs), addressing the challenges of personality consistency in personalized AI.
1 code implementation • 22 Nov 2023 • Zhicheng Yang, Yinya Huang, Jing Xiong, Liang Feng, Xiaodan Liang, Yiwei Wang, Jing Tang
Large Language Models prompting, such as using in-context demonstrations, is a mainstream technique for invoking LLMs to perform high-performance and solid complex reasoning (e. g., mathematical reasoning, commonsense reasoning), and has the potential for further human-machine collaborative scientific findings.
1 code implementation • 7 Nov 2023 • Yihong Luo, Siya Qiu, Xingjian Tao, Yujun Cai, Jing Tang
To address these issues, we introduce a conditional EBM for calibrating the generative direction of VAE during training, without requiring it for the generation at test time.
no code implementations • 21 Oct 2023 • Tianyuan Jin, Yu Yang, Jing Tang, Xiaokui Xiao, Pan Xu
Based on Tri-BBAI, we further propose the almost optimal batched best arm identification (Opt-BBAI) algorithm, which is the first algorithm that achieves the near-optimal sample and batch complexity in the non-asymptotic setting (i. e., $\delta>0$ is arbitrarily fixed), while enjoying the same batch and sample complexity as Tri-BBAI when $\delta$ tends to zero.
1 code implementation • 4 Oct 2023 • Jing Xiong, Zixuan Li, Chuanyang Zheng, Zhijiang Guo, Yichun Yin, Enze Xie, Zhicheng Yang, Qingxing Cao, Haiming Wang, Xiongwei Han, Jing Tang, Chengming Li, Xiaodan Liang
Dual Queries first query LLM to obtain LLM-generated knowledge such as CoT, then query the retriever to obtain the final exemplars via both question and the knowledge.
no code implementations • 21 Aug 2023 • Shuang Cui, Kai Han, Jing Tang, Xueying Li, Aakas Zhiyuli, Hanxiao Li
Submodular maximization has found extensive applications in various domains within the field of artificial intelligence, including but not limited to machine learning, computer vision, and natural language processing.
1 code implementation • 22 May 2023 • Yiwei Wang, Bryan Hooi, Fei Wang, Yujun Cai, Yuxuan Liang, Wenxuan Zhou, Jing Tang, Manjuan Duan, Muhao Chen
In principle, textual context determines the ground-truth relation and the RE models should be able to correctly identify the relations reflected by the textual context.
1 code implementation • 7 May 2023 • Yuhan Chen, Yihong Luo, Jing Tang, Liang Yang, Siya Qiu, Chuan Wang, Xiaochun Cao
Motivated by it, we propose to use the local similarity (LocalSim) to learn node-level weighted fusion, which can also serve as a plug-and-play module.
no code implementations • 30 Nov 2022 • Jing Tang, Bo Tao, Zeyu Gong, Zhouping Yin
Based on the drastic changes we found of the generalization error bound under different adversarial attacks and different training states, we proposed an adaptive training method which can greatly improve the image manipulation ability of multi-scale GANs.
1 code implementation • 2 Jul 2022 • Huimin Zhu, Renyi Zhou, Jing Tang, Min Li
The rational design of novel molecules with desired bioactivity is a critical but challenging task in drug discovery, especially when treating a novel target family or understudied targets.
no code implementations • 16 Jun 2022 • Tolou Shadbahr, Michael Roberts, Jan Stanczuk, Julian Gilbey, Philip Teare, Sören Dittmer, Matthew Thorpe, Ramon Vinas Torne, Evis Sala, Pietro Lio, Mishal Patel, AIX-COVNET Collaboration, James H. F. Rudd, Tuomas Mirtti, Antti Rannikko, John A. D. Aston, Jing Tang, Carola-Bibiane Schönlieb
Classifying samples in incomplete datasets is a common aim for machine learning practitioners, but is non-trivial.
no code implementations • 6 Mar 2022 • Yinghui Pan, Hanyi Zhang, Yifeng Zeng, Biyang Ma, Jing Tang, Zhong Ming
In this article, we investigate into diversifying behaviors of other agents in the subject agent's decision model prior to their interactions.
1 code implementation • 3 Dec 2021 • Ali Amiryousefi, Ville Kinnula, Jing Tang
The marginal Bayesian predictive classifiers (mBpc) as opposed to the simultaneous Bayesian predictive classifiers (sBpc), handle each data separately and hence tacitly assumes the independence of the observations.
no code implementations • 1 Dec 2021 • Yiwei Wang, Yujun Cai, Yuxuan Liang, Wei Wang, Henghui Ding, Muhao Chen, Jing Tang, Bryan Hooi
Representing a label distribution as a one-hot vector is a common practice in training node classification models.
no code implementations • 31 Oct 2021 • Jehad Aldahdooh, Ziaurrehman Tanoli, Jing Tang
Drug-target interactions (DTIs) are critical for drug discovery and repurposing, which are often manually extracted from the experimental articles.
Ranked #1 on
DrugProt
on DrugProt
2 code implementations • NeurIPS 2021 • Yining Ma, Jingwen Li, Zhiguang Cao, Wen Song, Le Zhang, Zhenghua Chen, Jing Tang
Moreover, the positional features are embedded through a novel cyclic positional encoding (CPE) method to allow Transformer to effectively capture the circularity and symmetry of VRP solutions (i. e., cyclic sequences).
1 code implementation • 2 Aug 2021 • Zhen Li, Jing Tang, Deqing Zou, Qian Chen, Shouhuai Xu, Chao Zhang, Yichen Li, Hai Jin
Automatically detecting software vulnerabilities in source code is an important problem that has attracted much attention.
no code implementations • 23 Sep 2020 • Kanglin Hsieh, Yinyin Wang, Luyao Chen, Zhongming Zhao, Sean Savitz, Xiaoqian Jiang, Jing Tang, Yejin Kim
In summary, we demonstrated that the integration of extensive interactions, deep neural networks, and rigorous validation can facilitate the rapid identification of candidate drugs for COVID-19 treatment.
no code implementations • 12 Aug 2020 • Jing Tang, Xueyan Tang, Andrew Lim, Kai Han, Chongshou Li, Junsong Yuan
Second, we enhance the modified greedy algorithm to derive a data-dependent upper bound on the optimum.
1 code implementation • 11 Aug 2020 • Xinke Li, Chongshou Li, Zekun Tong, Andrew Lim, Junsong Yuan, Yuwei Wu, Jing Tang, Raymond Huang
Based on it, we formulate a hierarchical learning problem for 3D point cloud segmentation and propose a measurement evaluating consistency across various hierarchies.
no code implementations • 27 May 2020 • Bilian Chen, Biyang Ma, Yifeng Zeng, Langcai Cao, Jing Tang
It is a concise knowledge representation that is well studied in a single-agent planning problem domain.
2 code implementations • 14 Apr 2020 • Keke Huang, Jing Tang, Kai Han, Xiaokui Xiao, Wei Chen, Aixin Sun, Xueyan Tang, Andrew Lim
In this paper, we propose the first practical algorithm for the adaptive IM problem that could provide the worst-case approximation guarantee of $1-\mathrm{e}^{\rho_b(\varepsilon-1)}$, where $\rho_b=1-(1-1/b)^b$ and $\varepsilon \in (0, 1)$ is a user-specified parameter.
Social and Information Networks
no code implementations • 13 Feb 2020 • Funan Mu, Zhenting Yu, LiFeng Wang, Yequan Wang, Qingyu Yin, Yibo Sun, Liqun Liu, Teng Ma, Jing Tang, Xing Zhou
In addition, with the help of tokens, our model is able to extract overlapped keyphrases.
no code implementations • 29 Dec 2019 • Yu An, Ying Ren, Jing Tang, Jun Chen, Baisong Chang
Metal nanoclusters (NCs), typically consisting of a few to tens of metal atoms, bridge the gap between organometallic compounds and crystalline metal nanoparticles.
1 code implementation • 24 Sep 2019 • Alberto Pessia, Jing Tang
To overcome this difficulty we will rewrite the transition probability in terms of a Gaussian hypergeometric function and subsequently obtain a three-term recurrence relation for its accurate evaluation.
Numerical Analysis Numerical Analysis Probability Methodology 65Q30 (Primary), 60J80 (Secondary), 33C05, 62F10, 62M05
no code implementations • ACL 2019 • Liqun Liu, Funan Mu, Pengyu Li, Xin Mu, Jing Tang, Xingsheng Ai, Ran Fu, LiFeng Wang, Xing Zhou
In this paper, we introduce NeuralClassifier, a toolkit for neural hierarchical multi-label text classification.
General Classification
Hierarchical Multi-label Classification
+5
no code implementations • 18 Sep 2018 • Reda Younsi, Jing Tang, Liisa Holm
Specialised fast algorithms for efficient bubble search are needed for coloured de bruijn graph variant calling applications.
Computational Engineering, Finance, and Science Genomics
1 code implementation • ACL 2018 • Wan-Ting Hsu, Chieh-Kai Lin, Ming-Ying Lee, Kerui Min, Jing Tang, Min Sun
On the one hand, a simple extractive model can obtain sentence-level attention with high ROUGE scores but less readable.
Ranked #39 on
Abstractive Text Summarization
on CNN / Daily Mail