Search Results for author: Ya-Qin Zhang

Found 46 papers, 26 papers with code

The Singapore Consensus on Global AI Safety Research Priorities

no code implementations25 Jun 2025 Yoshua Bengio, Tegan Maharaj, Luke Ong, Stuart Russell, Dawn Song, Max Tegmark, Lan Xue, Ya-Qin Zhang, Stephen Casper, Wan Sie Lee, Sören Mindermann, Vidhisha Balachandran, Fazl Barez, Michael Belinsky, Imane Bello, Malo Bourgon, Mark Brakel, Siméon Campos, Duncan Cass-Beggs, Jiahao Chen, Rumman Chowdhury, Kuan Chua Seah, Jeff Clune, Juntao Dai, Agnes Delaborde, Nouha Dziri, Francisco Eiras, Joshua Engels, Jinyu Fan, Adam Gleave, Noah Goodman, Fynn Heide, Dan Hendrycks, Cyrus Hodes, Bryan Low Kian Hsiang, Minlie Huang, Sami Jawhar, Wang Jingyu, Adam Tauman Kalai, Meindert Kamphuis, Mohan Kankanhalli, Subhash Kantamneni, Mathias Bonde Kirk, Thomas Kwa, Jeffrey Ladish, Kwok-Yan Lam, Wan Lee Sie, Taewhi Lee, Xiaojian Li, Jiajun Liu, Chaochao Lu, Yifan Mai, Richard Mallah, Julian Michael, Nick Moës, Simon Möller, Kihyuk Nam, Kwan Yee Ng, Mark Nitzberg, Besmira Nushi, Seán O hÉigeartaigh, Alejandro Ortega, Pierre Peigné, James Petrie, Benjamin Prud'homme, Reihaneh Rabbany, Nayat Sanchez-pi, Sarah Schwettmann, Buck Shlegeris, Saad Siddiqui, Aradhana Sinha, Martín Soto, Cheston Tan, Dong Ting, Robert Trager, Brian Tse, Anthony Tung K. H., Vanessa Wilfred, John Willes, Denise Wong, Wei Xu, Rongwu Xu, Yi Zeng, HongJiang Zhang, Djordje Žikelić

Rapidly improving AI capabilities and autonomy hold significant promise of transformation, but are also driving vigorous debate on how to ensure that AI is safe, i. e., trustworthy, reliable, and secure.

AANet: Virtual Screening under Structural Uncertainty via Alignment and Aggregation

no code implementations6 Jun 2025 Wenyu Zhu, Jianhui Wang, Bowen Gao, Yinjun Jia, Haichuan Tan, Ya-Qin Zhang, Wei-Ying Ma, Yanyan Lan

Virtual screening (VS) is a critical component of modern drug discovery, yet most existing methods--whether physics-based or deep learning-based--are developed around holo protein structures with known ligand-bound pockets.

Contrastive Learning Drug Discovery

PICD: Versatile Perceptual Image Compression with Diffusion Rendering

no code implementations CVPR 2025 Tongda Xu, Jiahao Li, Bin Li, Yan Wang, Ya-Qin Zhang, Yan Lu

To tackle this challenge, we propose versatile perceptual screen image compression with diffusion rendering (PICD), a codec that works well for both screen and natural images.

Image Compression

PharmAgents: Building a Virtual Pharma with Large Language Model Agents

no code implementations28 Mar 2025 Bowen Gao, Yanwen Huang, Yiqiao Liu, Wenxuan Xie, Wei-Ying Ma, Ya-Qin Zhang, Yanyan Lan

The discovery of novel small molecule drugs remains a critical scientific challenge with far-reaching implications for treating diseases and advancing human health.

Drug Discovery Language Modeling +2

Pushing the boundaries of Structure-Based Drug Design through Collaboration with Large Language Models

no code implementations3 Mar 2025 Bowen Gao, Yanwen Huang, Yiqiao Liu, Wenxuan Xie, Wei-Ying Ma, Ya-Qin Zhang, Yanyan Lan

Structure-Based Drug Design (SBDD) has revolutionized drug discovery by enabling the rational design of molecules for specific protein targets.

Drug Design Drug Discovery

CoopDETR: A Unified Cooperative Perception Framework for 3D Detection via Object Query

no code implementations26 Feb 2025 Zhe Wang, Shaocong Xu, Xucai Zhuang, Tongda Xu, Yan Wang, Jingjing Liu, Yilun Chen, Ya-Qin Zhang

Cooperative perception enhances the individual perception capabilities of autonomous vehicles (AVs) by providing a comprehensive view of the environment.

Autonomous Vehicles Object

Contrastive Private Data Synthesis via Weighted Multi-PLM Fusion

no code implementations1 Feb 2025 Tianyuan Zou, Yang Liu, Peng Li, Yufei Xiong, Jianqing Zhang, Jingjing Liu, Xiaozhou Ye, Ye Ouyang, Ya-Qin Zhang

WASP utilizes limited private samples for more accurate private data distribution estimation via a Top-Q voting mechanism, and leverages low-quality synthetic samples for contrastive generation via collaboration among dynamically weighted multiple pre-trained models. Extensive experiments on 6 well-developed datasets with 6 open-source and 3 closed-source PLMs demonstrate the superiority of WASP in improving model performance over diverse downstream tasks.

Rethinking Diffusion Posterior Sampling: From Conditional Score Estimator to Maximizing a Posterior

1 code implementation31 Jan 2025 Tongda Xu, Xiyan Cai, Xinjie Zhang, Xingtong Ge, Dailan He, Ming Sun, Jingjing Liu, Ya-Qin Zhang, Jian Li, Yan Wang

Recent advancements in diffusion models have been leveraged to address inverse problems without additional training, and Diffusion Posterior Sampling (DPS) (Chung et al., 2022a) is among the most popular approaches.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain

no code implementations30 Jan 2025 Zhe Wang, Xiaoliang Huo, Siqi Fan, Jingjing Liu, Ya-Qin Zhang, Yan Wang

In-Domain Query Interaction module utilizes a transformer to learn content and depth information for each domain and outputs object queries.

Autonomous Driving Contrastive Learning +2

International AI Safety Report

no code implementations29 Jan 2025 Yoshua Bengio, Sören Mindermann, Daniel Privitera, Tamay Besiroglu, Rishi Bommasani, Stephen Casper, Yejin Choi, Philip Fox, Ben Garfinkel, Danielle Goldfarb, Hoda Heidari, Anson Ho, Sayash Kapoor, Leila Khalatbari, Shayne Longpre, Sam Manning, Vasilios Mavroudis, Mantas Mazeika, Julian Michael, Jessica Newman, Kwan Yee Ng, Chinasa T. Okolo, Deborah Raji, Girish Sastry, Elizabeth Seger, Theodora Skeadas, Tobin South, Emma Strubell, Florian Tramèr, Lucia Velasco, Nicole Wheeler, Daron Acemoglu, Olubayo Adekanmbi, David Dalrymple, Thomas G. Dietterich, Edward W. Felten, Pascale Fung, Pierre-Olivier Gourinchas, Fredrik Heintz, Geoffrey Hinton, Nick Jennings, Andreas Krause, Susan Leavy, Percy Liang, Teresa Ludermir, Vidushi Marda, Helen Margetts, John McDermid, Jane Munga, Arvind Narayanan, Alondra Nelson, Clara Neppel, Alice Oh, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Bernhard Schölkopf, Dawn Song, Alvaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Ya-Qin Zhang, Fahad Albalawi, Marwan Alserkal, Olubunmi Ajala, Guillaume Avrin, Christian Busch, André Carlos Ponce de Leon Ferreira de Carvalho, Bronwyn Fox, Amandeep Singh Gill, Ahmet Halit Hatip, Juha Heikkilä, Gill Jolly, Ziv Katzir, Hiroaki Kitano, Antonio Krüger, Chris Johnson, Saif M. Khan, Kyoung Mu Lee, Dominic Vincent Ligot, Oleksii Molchanovskyi, Andrea Monti, Nusu Mwamanzi, Mona Nemer, Nuria Oliver, José Ramón López Portillo, Balaraman Ravindran, Raquel Pezoa Rivera, Hammam Riza, Crystal Rugege, Ciarán Seoighe, Jerry Sheehan, Haroon Sheikh, Denise Wong, Yi Zeng

The first International AI Safety Report comprehensively synthesizes the current evidence on the capabilities, risks, and safety of advanced AI systems.

AutoDroid-V2: Boosting SLM-based GUI Agents via Code Generation

1 code implementation24 Dec 2024 Hao Wen, Shizuo Tian, Borislav Pavlov, Wenjie Du, Yixuan Li, Ge Chang, Shanhui Zhao, Jiacheng Liu, Yunxin Liu, Ya-Qin Zhang, Yuanchun Li

Unlike normal coding tasks that can be extensively pre-trained with public datasets, generating UI automation code is challenging due to the diversity, complexity, and variability of target apps.

Code Generation

Robo-MUTUAL: Robotic Multimodal Task Specification via Unimodal Learning

no code implementations2 Oct 2024 Jianxiong Li, Zhihao Wang, Jinliang Zheng, Xiaoai Zhou, Guanming Wang, Guanglu Song, Yu Liu, Jingjing Liu, Ya-Qin Zhang, Junzhi Yu, Xianyuan Zhan

Multimodal task specification is essential for enhanced robotic performance, where \textit{Cross-modality Alignment} enables the robot to holistically understand complex task instructions.

FuseGen: PLM Fusion for Data-generation based Zero-shot Learning

1 code implementation18 Jun 2024 Tianyuan Zou, Yang Liu, Peng Li, Jianqing Zhang, Jingjing Liu, Ya-Qin Zhang

To mitigate such bias, we propose FuseGen, a novel data generation-based zero-shot learning framework that introduces a new criteria for subset selection from synthetic datasets via utilizing multiple PLMs and trained STMs.

Zero-Shot Learning

From Theory to Therapy: Reframing SBDD Model Evaluation via Practical Metrics

1 code implementation13 Jun 2024 Bowen Gao, Haichuan Tan, Yanwen Huang, Minsi Ren, Xiao Huang, Wei-Ying Ma, Ya-Qin Zhang, Yanyan Lan

Recent advancements in structure-based drug design (SBDD) have significantly enhanced the efficiency and precision of drug discovery by generating molecules tailored to bind specific protein pockets.

Drug Design Drug Discovery

SIU: A Million-Scale Structural Small Molecule-Protein Interaction Dataset for Unbiased Bioactivity Prediction

1 code implementation13 Jun 2024 Yanwen Huang, Bowen Gao, Yinjun Jia, Hongbo Ma, Wei-Ying Ma, Ya-Qin Zhang, Yanyan Lan

Small molecules play a pivotal role in modern medicine, and scrutinizing their interactions with protein targets is essential for the discovery and development of novel, life-saving therapeutics.

Prediction

Agent Hospital: A Simulacrum of Hospital with Evolvable Medical Agents

no code implementations5 May 2024 Junkai Li, Yunghwei Lai, Weitao Li, Jingyi Ren, Meng Zhang, Xinhui Kang, Siyu Wang, Peng Li, Ya-Qin Zhang, Weizhi Ma, Yang Liu

The recent rapid development of large language models (LLMs) has sparked a new wave of technological revolution in medical artificial intelligence (AI).

MedQA Question Answering

DecisionNCE: Embodied Multimodal Representations via Implicit Preference Learning

1 code implementation28 Feb 2024 Jianxiong Li, Jinliang Zheng, Yinan Zheng, Liyuan Mao, Xiao Hu, Sijie Cheng, Haoyi Niu, Jihao Liu, Yu Liu, Jingjing Liu, Ya-Qin Zhang, Xianyuan Zhan

Multimodal pretraining is an effective strategy for the trinity of goals of representation learning in autonomous robots: 1) extracting both local and global task progressions; 2) enforcing temporal consistency of visual representation; 3) capturing trajectory-level language grounding.

Contrastive Learning Decision Making +1

EMIFF: Enhanced Multi-scale Image Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object Detection

2 code implementations23 Feb 2024 Zhe Wang, Siqi Fan, Xiaoliang Huo, Tongda Xu, Yan Wang, Jingjing Liu, Yilun Chen, Ya-Qin Zhang

In autonomous driving, cooperative perception makes use of multi-view cameras from both vehicles and infrastructure, providing a global vantage point with rich semantic context of road conditions beyond a single vehicle viewpoint.

3D Object Detection Autonomous Driving +2

Consistency Model is an Effective Posterior Sample Approximation for Diffusion Inverse Solvers

no code implementations9 Feb 2024 Tongda Xu, Ziran Zhu, Jian Li, Dailan He, Yuanyuan Wang, Ming Sun, Ling Li, Hongwei Qin, Yan Wang, Jingjing Liu, Ya-Qin Zhang

Diffusion Inverse Solvers (DIS) are designed to sample from the conditional distribution $p_{\theta}(X_0|y)$, with a predefined diffusion model $p_{\theta}(X_0)$, an operator $f(\cdot)$, and a measurement $y=f(x'_0)$ derived from an unknown image $x'_0$.

Image Captioning Semantic Segmentation

Idempotence and Perceptual Image Compression

1 code implementation17 Jan 2024 Tongda Xu, Ziran Zhu, Dailan He, Yanghao Li, Lina Guo, Yuanyuan Wang, Zhe Wang, Hongwei Qin, Yan Wang, Jingjing Liu, Ya-Qin Zhang

However, we find that theoretically: 1) Conditional generative model-based perceptual codec satisfies idempotence; 2) Unconditional generative model with idempotence constraint is equivalent to conditional generative codec.

Image Compression

Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security

2 code implementations10 Jan 2024 Yuanchun Li, Hao Wen, Weijun Wang, Xiangyu Li, Yizhen Yuan, Guohong Liu, Jiacheng Liu, Wenxing Xu, Xiang Wang, Yi Sun, Rui Kong, Yile Wang, Hanfei Geng, Jian Luan, Xuefeng Jin, Zilong Ye, Guanjing Xiong, Fan Zhang, Xiang Li, Mengwei Xu, Zhijun Li, Peng Li, Yang Liu, Ya-Qin Zhang, Yunxin Liu

Next, we discuss several key challenges to achieve intelligent, efficient and secure Personal LLM Agents, followed by a comprehensive survey of representative solutions to address these challenges.

Task Planning

VFLAIR: A Research Library and Benchmark for Vertical Federated Learning

1 code implementation15 Oct 2023 Tianyuan Zou, Zixuan Gu, Yu He, Hideaki Takahashi, Yang Liu, Ya-Qin Zhang

Vertical Federated Learning (VFL) has emerged as a collaborative training paradigm that allows participants with different features of the same group of users to accomplish cooperative training without exposing their raw data or model parameters.

Vertical Federated Learning

Distributional Soft Actor-Critic with Three Refinements

2 code implementations9 Oct 2023 Jingliang Duan, Wenxuan Wang, Liming Xiao, Jiaxin Gao, Shengbo Eben Li, Chang Liu, Ya-Qin Zhang, Bo Cheng, Keqiang Li

To address this issue, we previously proposed the Distributional Soft Actor-Critic (DSAC or DSACv1), an off-policy RL algorithm that enhances value estimation accuracy by learning a continuous Gaussian value distribution.

Decision Making Reinforcement Learning (RL)

Conditional Perceptual Quality Preserving Image Compression

no code implementations16 Aug 2023 Tongda Xu, Qian Zhang, Yanghao Li, Dailan He, Zhe Wang, Yuanyuan Wang, Hongwei Qin, Yan Wang, Jingjing Liu, Ya-Qin Zhang

We propose conditional perceptual quality, an extension of the perceptual quality defined in \citet{blau2018perception}, by conditioning it on user defined information.

Image Compression

Query-Policy Misalignment in Preference-Based Reinforcement Learning

1 code implementation27 May 2023 Xiao Hu, Jianxiong Li, Xianyuan Zhan, Qing-Shan Jia, Ya-Qin Zhang

To unravel this mystery, we identify a long-neglected issue in the query selection schemes of existing PbRL studies: Query-Policy Misalignment.

reinforcement-learning Reinforcement Learning

PROTO: Iterative Policy Regularized Offline-to-Online Reinforcement Learning

1 code implementation25 May 2023 Jianxiong Li, Xiao Hu, Haoran Xu, Jingjing Liu, Xianyuan Zhan, Ya-Qin Zhang

Offline-to-online reinforcement learning (RL), by combining the benefits of offline pretraining and online finetuning, promises enhanced sample efficiency and policy performance.

Computational Efficiency reinforcement-learning +2

Feasible Policy Iteration for Safe Reinforcement Learning

no code implementations18 Apr 2023 Yujie Yang, Zhilong Zheng, Shengbo Eben Li, Wei Xu, Jingjing Liu, Xianyuan Zhan, Ya-Qin Zhang

A region-wise update rule is developed for the policy improvement step, which maximizes state-value function inside the feasible region and minimizes feasibility function outside it.

reinforcement-learning Reinforcement Learning +2

DPF: Learning Dense Prediction Fields with Weak Supervision

1 code implementation CVPR 2023 Xiaoxue Chen, Yuhang Zheng, Yupeng Zheng, Qiang Zhou, Hao Zhao, Guyue Zhou, Ya-Qin Zhang

We showcase the effectiveness of DPFs using two substantially different tasks: high-level semantic parsing and low-level intrinsic image decomposition.

Intrinsic Image Decomposition Prediction +2

VIMI: Vehicle-Infrastructure Multi-view Intermediate Fusion for Camera-based 3D Object Detection

2 code implementations20 Mar 2023 Zhe Wang, Siqi Fan, Xiaoliang Huo, Tongda Xu, Yan Wang, Jingjing Liu, Yilun Chen, Ya-Qin Zhang

In autonomous driving, Vehicle-Infrastructure Cooperative 3D Object Detection (VIC3D) makes use of multi-view cameras from both vehicles and traffic infrastructure, providing a global vantage point with rich semantic context of road conditions beyond a single vehicle viewpoint.

3D Object Detection Autonomous Driving +2

AdaptiveNet: Post-deployment Neural Architecture Adaptation for Diverse Edge Environments

no code implementations13 Mar 2023 Hao Wen, Yuanchun Li, Zunshuai Zhang, Shiqi Jiang, Xiaozhou Ye, Ye Ouyang, Ya-Qin Zhang, Yunxin Liu

Model elastification generates a high-quality search space of model architectures with the guidance of a developer-specified oracle model.

valid

LODE: Locally Conditioned Eikonal Implicit Scene Completion from Sparse LiDAR

1 code implementation27 Feb 2023 Pengfei Li, Ruowen Zhao, Yongliang Shi, Hao Zhao, Jirui Yuan, Guyue Zhou, Ya-Qin Zhang

In this paper, we propose a novel Eikonal formulation that conditions the implicit representation on localized shape priors which function as dense boundary value constraints, and demonstrate it works on SemanticKITTI and SemanticPOSS.

Autonomous Driving Representation Learning

Mind the Gap: Offline Policy Optimization for Imperfect Rewards

1 code implementation3 Feb 2023 Jianxiong Li, Xiao Hu, Haoran Xu, Jingjing Liu, Xianyuan Zhan, Qing-Shan Jia, Ya-Qin Zhang

RGM is formulated as a bi-level optimization problem: the upper layer optimizes a reward correction term that performs visitation distribution matching w. r. t.

Reinforcement Learning (RL)

Mutual Information Regularization for Vertical Federated Learning

no code implementations1 Jan 2023 Tianyuan Zou, Yang Liu, Ya-Qin Zhang

However, previous works show that parties without labels (passive parties) in VFL can infer the sensitive label information owned by the party with labels (active party) or execute backdoor attacks to VFL.

Vertical Federated Learning

Vertical Federated Learning: Concepts, Advances and Challenges

no code implementations23 Nov 2022 Yang Liu, Yan Kang, Tianyuan Zou, Yanhong Pu, Yuanqin He, Xiaozhou Ye, Ye Ouyang, Ya-Qin Zhang, Qiang Yang

Motivated by the rapid growth in VFL research and real-world applications, we provide a comprehensive review of the concept and algorithms of VFL, as well as current advances and challenges in various aspects, including effectiveness, efficiency, and privacy.

Fairness Privacy Preserving +1

TOIST: Task Oriented Instance Segmentation Transformer with Noun-Pronoun Distillation

1 code implementation19 Oct 2022 Pengfei Li, Beiwen Tian, Yongliang Shi, Xiaoxue Chen, Hao Zhao, Guyue Zhou, Ya-Qin Zhang

As such, we study the challenging problem of task oriented detection, which aims to find objects that best afford an action indicated by verbs like sit comfortably on.

Instance Segmentation Referring Expression +2

When Data Geometry Meets Deep Function: Generalizing Offline Reinforcement Learning

2 code implementations23 May 2022 Jianxiong Li, Xianyuan Zhan, Haoran Xu, Xiangyu Zhu, Jingjing Liu, Ya-Qin Zhang

In offline reinforcement learning (RL), one detrimental issue to policy learning is the error accumulation of deep Q function in out-of-distribution (OOD) areas.

D4RL Offline RL +3

Semi-supervised Implicit Scene Completion from Sparse LiDAR

1 code implementation29 Nov 2021 Pengfei Li, Yongliang Shi, Tianyu Liu, Hao Zhao, Guyue Zhou, Ya-Qin Zhang

Recent advances show that semi-supervised implicit representation learning can be achieved through physical constraints like Eikonal equations.

Representation Learning

Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing

1 code implementation CVPR 2022 Xiaoxue Chen, Tianyu Liu, Hao Zhao, Guyue Zhou, Ya-Qin Zhang

Multi-task indoor scene understanding is widely considered as an intriguing formulation, as the affinity of different tasks may lead to improved performance.

Attribute Scene Understanding +2

PQ-Transformer: Jointly Parsing 3D Objects and Layouts from Point Clouds

1 code implementation12 Sep 2021 Xiaoxue Chen, Hao Zhao, Guyue Zhou, Ya-Qin Zhang

Such a scheme has two limitations: 1) Storing and running several networks for different tasks are expensive for typical robotic platforms.

object-detection Object Detection +2

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