no code implementations • 6 Apr 2025 • Cheng Chang, Jingwei Ge, Jiazhe Guo, Zelin Guo, Binghong Jiang, Li Li
Driving scenario data play an increasingly vital role in the development of intelligent vehicles and autonomous driving.
no code implementations • 21 Feb 2025 • Yingying Sun, Jun A, Zhiwei Liu, Rui Sun, Liujia Qian, Samuel H. Payne, Wout Bittremieux, Markus Ralser, Chen Li, Yi Chen, Zhen Dong, Yasset Perez-Riverol, Asif Khan, Chris Sander, Ruedi Aebersold, Juan Antonio Vizcaíno, Jonathan R Krieger, Jianhua Yao, Han Wen, Linfeng Zhang, Yunping Zhu, Yue Xuan, Benjamin Boyang Sun, Liang Qiao, Henning Hermjakob, Haixu Tang, Huanhuan Gao, Yamin Deng, Qing Zhong, Cheng Chang, Nuno Bandeira, Ming Li, Weinan E, Siqi Sun, Yuedong Yang, Gilbert S. Omenn, Yue Zhang, Ping Xu, Yan Fu, Xiaowen Liu, Christopher M. Overall, Yu Wang, Eric W. Deutsch, Luonan Chen, Jürgen Cox, Vadim Demichev, Fuchu He, Jiaxing Huang, Huilin Jin, Chao Liu, Nan Li, Zhongzhi Luan, Jiangning Song, Kaicheng Yu, Wanggen Wan, Tai Wang, Kang Zhang, Le Zhang, Peter A. Bell, Matthias Mann, Bing Zhang, Tiannan Guo
Artificial intelligence (AI) is transforming scientific research, including proteomics.
1 code implementation • 10 Nov 2024 • Yu Gu, Kai Zhang, Yuting Ning, Boyuan Zheng, Boyu Gou, Tianci Xue, Cheng Chang, Sanjari Srivastava, Yanan Xie, Peng Qi, Huan Sun, Yu Su
We advocate model-based planning for web agents that employs a world model to simulate and deliberate over the outcome of each candidate action before committing to one.
no code implementations • 7 Nov 2024 • Yichen Shi, Zhuofu Tao, Yuhao Gao, Tianjia Zhou, Cheng Chang, Yaxing Wang, BingYu Chen, Genhao Zhang, Alvin Liu, Zhiping Yu, Ting-Jung Lin, Lei He
A significant portion of the effort is experience-driven, which makes the automation of AMS circuit design a formidable challenge.
1 code implementation • 7 Oct 2024 • Boyu Gou, Ruohan Wang, Boyuan Zheng, Yanan Xie, Cheng Chang, Yiheng Shu, Huan Sun, Yu Su
The key is visual grounding models that can accurately map diverse referring expressions of GUI elements to their coordinates on the GUI across different platforms.
Ranked #1 on
Natural Language Visual Grounding
on ScreenSpot
no code implementations • 1 Jul 2024 • Ryan Louie, Ananjan Nandi, William Fang, Cheng Chang, Emma Brunskill, Diyi Yang
To address this, we develop Roleplay-doh, a novel human-LLM collaboration pipeline that elicits qualitative feedback from a domain-expert, which is transformed into a set of principles, or natural language rules, that govern an LLM-prompted roleplay.
1 code implementation • 21 May 2024 • Zhangyue Yin, Qiushi Sun, Qipeng Guo, Zhiyuan Zeng, Xiaonan Li, Tianxiang Sun, Cheng Chang, Qinyuan Cheng, Ding Wang, Xiaofeng Mou, Xipeng Qiu, Xuanjing Huang
Recent advancements in Chain-of-Thought prompting have facilitated significant breakthroughs for Large Language Models (LLMs) in complex reasoning tasks.
1 code implementation • 18 Dec 2023 • Zhi Jin, Sheng Xu, Xiang Zhang, Tianze Ling, Nanqing Dong, Wanli Ouyang, Zhiqiang Gao, Cheng Chang, Siqi Sun
De novo peptide sequencing from mass spectrometry (MS) data is a critical task in proteomics research.
no code implementations • 10 Dec 2023 • Cheng Chang, Zhouping Xin, Tieyong Zeng
However, when the spatial dimension is one, the original curl-free relaxation component is inapplicable, and the approximation formula for dummy variables, which works well in a 2-dimensional scenario, fails to provide a reasonable output in the 1-dimensional case.
1 code implementation • 4 Dec 2023 • Zhangyue Yin, Qiushi Sun, Cheng Chang, Qipeng Guo, Junqi Dai, Xuanjing Huang, Xipeng Qiu
Large Language Models (LLMs) have recently made significant strides in complex reasoning tasks through the Chain-of-Thought technique.
1 code implementation • bioRxiv 2023 • Tingpeng Yang, Tianze Ling, Boyan Sun, Zhendong Liang, Fan Xu, Xiansong Huang, Linhai Xie, Yonghong He, Leyuan Li, Fuchu He, Yu Wang, Cheng Chang
De novo peptide sequencing is a promising approach for novel peptide discovery.
1 code implementation • 11 Jul 2023 • Rui Zheng, Shihan Dou, Songyang Gao, Yuan Hua, Wei Shen, Binghai Wang, Yan Liu, Senjie Jin, Qin Liu, Yuhao Zhou, Limao Xiong, Lu Chen, Zhiheng Xi, Nuo Xu, Wenbin Lai, Minghao Zhu, Cheng Chang, Zhangyue Yin, Rongxiang Weng, Wensen Cheng, Haoran Huang, Tianxiang Sun, Hang Yan, Tao Gui, Qi Zhang, Xipeng Qiu, Xuanjing Huang
Therefore, we explore the PPO-max, an advanced version of PPO algorithm, to efficiently improve the training stability of the policy model.
no code implementations • 13 May 2022 • Cheng Chang, Tieyong Zeng
The proposed model learns from both data and physics constraints through the training of a deep neural network, which serves as part of the covariance function in GPR.
no code implementations • 23 Oct 2020 • Yuhan Zhang, Cheng Chang
This paper models the US-China trade conflict and attempts to analyze the (optimal) strategic choices.
no code implementations • 12 Dec 2019 • Yichao Lu, Cheng Chang, Himanshu Rai, Guangwei Yu, Maksims Volkovs
We present our winning solution to the Open Images 2019 Visual Relationship challenge.
1 code implementation • NeurIPS 2019 • Chundi Liu, Guangwei Yu, Maksims Volkovs, Cheng Chang, Himanshu Rai, Junwei Ma, Satya Krishna Gorti
Despite recent progress in computer vision, image retrieval remains a challenging open problem.
no code implementations • 12 Jun 2019 • Cheng Chang, Himanshu Rai, Satya Krishna Gorti, Junwei Ma, Chundi Liu, Guangwei Yu, Maksims Volkovs
We present our solution to Landmark Image Retrieval Challenge 2019.
1 code implementation • CVPR 2019 • Cheng Chang, Guangwei Yu, Chundi Liu, Maksims Volkovs
Given a nearest neighbor graph produced by the global descriptor model, we traverse it by alternating between exploit and explore steps.
no code implementations • WS 2018 • Kaige Xie, Cheng Chang, Liliang Ren, Lu Chen, Kai Yu
Dialogue state tracking (DST), when formulated as a supervised learning problem, relies on labelled data.
2 code implementations • 19 Dec 2017 • Alex Levinshtein, Cheng Chang, Edmund Phung, Irina Kezele, Wenzhangzhi Guo, Parham Aarabi
Augmented reality is an emerging technology in many application domains.
no code implementations • EMNLP 2017 • Lu Chen, Xiang Zhou, Cheng Chang, Runzhe Yang, Kai Yu
Hand-crafted rules and reinforcement learning (RL) are two popular choices to obtain dialogue policy.
no code implementations • EMNLP 2017 • Cheng Chang, Runzhe Yang, Lu Chen, Xiang Zhou, Kai Yu
The key to building an evolvable dialogue system in real-world scenarios is to ensure an affordable on-line dialogue policy learning, which requires the on-line learning process to be safe, efficient and economical.
no code implementations • EACL 2017 • Lu Chen, Runzhe Yang, Cheng Chang, Zihao Ye, Xiang Zhou, Kai Yu
On-line dialogue policy learning is the key for building evolvable conversational agent in real world scenarios.