Search Results for author: Jiankai Sun

Found 37 papers, 16 papers with code

Leveraging Print Debugging to Improve Code Generation in Large Language Models

no code implementations10 Jan 2024 Xueyu Hu, Kun Kuang, Jiankai Sun, Hongxia Yang, Fei Wu

Large language models (LLMs) have made significant progress in code generation tasks, but their performance in tackling programming problems with complex data structures and algorithms remains suboptimal.

Code Generation In-Context Learning

Aria-NeRF: Multimodal Egocentric View Synthesis

no code implementations11 Nov 2023 Jiankai Sun, Jianing Qiu, Chuanyang Zheng, John Tucker, Javier Yu, Mac Schwager

The construction of a NeRF-like model from an egocentric image sequence plays a pivotal role in understanding human behavior and holds diverse applications within the realms of VR/AR.

Lyra: Orchestrating Dual Correction in Automated Theorem Proving

1 code implementation27 Sep 2023 Chuanyang Zheng, Haiming Wang, Enze Xie, Zhengying Liu, Jiankai Sun, Huajian Xin, Jianhao Shen, Zhenguo Li, Yu Li

In addition, we introduce Conjecture Correction, an error feedback mechanism designed to interact with prover to refine formal proof conjectures with prover error messages.

 Ranked #1 on Automated Theorem Proving on miniF2F-test (Pass@100 metric)

Automated Theorem Proving Hallucination

Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems

no code implementations25 May 2023 Xiaohui Chen, Jiankai Sun, Taiqing Wang, Ruocheng Guo, Li-Ping Liu, Aonan Zhang

Most subsampling methods are model-based and often require a pre-trained pilot model to measure data importance via e. g. sample hardness.

Recommendation Systems

Large AI Models in Health Informatics: Applications, Challenges, and the Future

1 code implementation21 Mar 2023 Jianing Qiu, Lin Li, Jiankai Sun, Jiachuan Peng, Peilun Shi, Ruiyang Zhang, Yinzhao Dong, Kyle Lam, Frank P. -W. Lo, Bo Xiao, Wu Yuan, Ningli Wang, Dong Xu, Benny Lo

Large AI models, or foundation models, are models recently emerging with massive scales both parameter-wise and data-wise, the magnitudes of which can reach beyond billions.

Decision Making Drug Discovery +1

Netflix and Forget: Efficient and Exact Machine Unlearning from Bi-linear Recommendations

no code implementations13 Feb 2023 Mimee Xu, Jiankai Sun, Xin Yang, Kevin Yao, Chong Wang

Without incurring the cost of re-training, and without degrading the model unnecessarily, we develop Unlearn-ALS by making a few key modifications to the fine-tuning procedure under Alternating Least Squares optimisation, thus applicable to any bi-linear models regardless of the training procedure.

Machine Unlearning Matrix Completion

Label Inference Attack against Split Learning under Regression Setting

1 code implementation18 Jan 2023 Shangyu Xie, Xin Yang, Yuanshun Yao, Tianyi Liu, Taiqing Wang, Jiankai Sun

In this work, we step further to study the leakage in the scenario of the regression model, where the private labels are continuous numbers (instead of discrete labels in classification).

Inference Attack regression +1

DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation

1 code implementation18 Nov 2022 Liangwei Yang, Shengjie Wang, Yunzhe Tao, Jiankai Sun, Xiaolong Liu, Philip S. Yu, Taiqing Wang

Graph Neural Network (GNN) based recommender systems have been attracting more and more attention in recent years due to their excellent performance in accuracy.

Graph Neural Network Recommendation Systems

Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes

1 code implementation6 Oct 2022 Zhaowei Zhu, Yuanshun Yao, Jiankai Sun, Hang Li, Yang Liu

Our theoretical analyses show that directly using proxy models can give a false sense of (un)fairness.


NeRF-Loc: Transformer-Based Object Localization Within Neural Radiance Fields

no code implementations24 Sep 2022 Jiankai Sun, Yan Xu, Mingyu Ding, Hongwei Yi, Chen Wang, Jingdong Wang, Liangjun Zhang, Mac Schwager

Using current NeRF training tools, a robot can train a NeRF environment model in real-time and, using our algorithm, identify 3D bounding boxes of objects of interest within the NeRF for downstream navigation or manipulation tasks.

Object Localization Robot Navigation

DPAUC: Differentially Private AUC Computation in Federated Learning

1 code implementation25 Aug 2022 Jiankai Sun, Xin Yang, Yuanshun Yao, Junyuan Xie, Di wu, Chong Wang

Federated learning (FL) has gained significant attention recently as a privacy-enhancing tool to jointly train a machine learning model by multiple participants.

Federated Learning

Differentially Private Multi-Party Data Release for Linear Regression

no code implementations16 Jun 2022 Ruihan Wu, Xin Yang, Yuanshun Yao, Jiankai Sun, Tianyi Liu, Kilian Q. Weinberger, Chong Wang

Differentially Private (DP) data release is a promising technique to disseminate data without compromising the privacy of data subjects.


Differentially Private AUC Computation in Vertical Federated Learning

no code implementations24 May 2022 Jiankai Sun, Xin Yang, Yuanshun Yao, Junyuan Xie, Di wu, Chong Wang

In this work, we propose two evaluation algorithms that can more accurately compute the widely used AUC (area under curve) metric when using label DP in vFL.

Vertical Federated Learning

LocATe: End-to-end Localization of Actions in 3D with Transformers

no code implementations21 Mar 2022 Jiankai Sun, Bolei Zhou, Michael J. Black, Arjun Chandrasekaran

An important component of this problem is 3D Temporal Action Localization (3D-TAL), which involves recognizing what actions a person is performing, and when.

Action Recognition object-detection +2

Differentially Private Label Protection in Split Learning

no code implementations4 Mar 2022 Xin Yang, Jiankai Sun, Yuanshun Yao, Junyuan Xie, Chong Wang

Split learning is a distributed training framework that allows multiple parties to jointly train a machine learning model over vertically partitioned data (partitioned by attributes).

Label Leakage and Protection from Forward Embedding in Vertical Federated Learning

no code implementations2 Mar 2022 Jiankai Sun, Xin Yang, Yuanshun Yao, Chong Wang

As the raw labels often contain highly sensitive information, some recent work has been proposed to prevent the label leakage from the backpropagated gradients effectively in vFL.

Vertical Federated Learning

Egocentric Human Trajectory Forecasting with a Wearable Camera and Multi-Modal Fusion

1 code implementation1 Nov 2021 Jianing Qiu, Lipeng Chen, Xiao Gu, Frank P. -W. Lo, Ya-Yen Tsai, Jiankai Sun, Jiaqi Liu, Benny Lo

To this end, a novel egocentric human trajectory forecasting dataset was constructed, containing real trajectories of people navigating in crowded spaces wearing a camera, as well as extracted rich contextual data.

Decoder Trajectory Forecasting

Defending against Reconstruction Attack in Vertical Federated Learning

no code implementations21 Jul 2021 Jiankai Sun, Yuanshun Yao, Weihao Gao, Junyuan Xie, Chong Wang

Recently researchers have studied input leakage problems in Federated Learning (FL) where a malicious party can reconstruct sensitive training inputs provided by users from shared gradient.

Privacy Preserving Reconstruction Attack +1

Vertical Federated Learning without Revealing Intersection Membership

no code implementations10 Jun 2021 Jiankai Sun, Xin Yang, Yuanshun Yao, Aonan Zhang, Weihao Gao, Junyuan Xie, Chong Wang

In this paper, we propose a vFL framework based on Private Set Union (PSU) that allows each party to keep sensitive membership information to itself.

Vertical Federated Learning

Deep Retrieval: An End-to-End Structure Model for Large-Scale Recommendations

1 code implementation1 Jan 2021 Weihao Gao, Xiangjun Fan, Jiankai Sun, Kai Jia, Wenzhi Xiao, Chong Wang, Xiaobing Liu

With the model learnt, a beam search over the latent codes is performed to retrieve the top candidates.


Transferable Active Grasping and Real Embodied Dataset

1 code implementation28 Apr 2020 Xiangyu Chen, Zelin Ye, Jiankai Sun, Yuda Fan, Fang Hu, Chenxi Wang, Cewu Lu

Grasping in cluttered scenes is challenging for robot vision systems, as detection accuracy can be hindered by partial occlusion of objects.

Reinforcement Learning (RL)

Learning a Decision Module by Imitating Driver's Control Behaviors

no code implementations30 Nov 2019 Junning Huang, Sirui Xie, Jiankai Sun, Qiurui Ma, Chunxiao Liu, Jianping Shi, Dahua Lin, Bolei Zhou

In this work, we propose a hybrid framework to learn neural decisions in the classical modular pipeline through end-to-end imitation learning.

Autonomous Driving Imitation Learning

An End-to-End Framework for Cold Question Routing in Community Question Answering Services

no code implementations22 Nov 2019 Jiankai Sun, Jie Zhao, Huan Sun, Srinivasan Parthasarathy

Routing newly posted questions (a. k. a cold questions) to potential answerers with the suitable expertise in Community Question Answering sites (CQAs) is an important and challenging task.

Community Question Answering Graph Embedding

Learning with Social Influence through Interior Policy Differentiation

no code implementations25 Sep 2019 Hao Sun, Bo Dai, Jiankai Sun, Zhenghao Peng, Guodong Xu, Dahua Lin, Bolei Zhou

In this work we model the social influence into the scheme of reinforcement learning, enabling the agents to learn both from the environment and from their peers.

Reinforcement Learning (RL)

GDRQ: Group-based Distribution Reshaping for Quantization

no code implementations5 Aug 2019 Haibao Yu, Tuopu Wen, Guangliang Cheng, Jiankai Sun, Qi Han, Jianping Shi

Low-bit quantization is challenging to maintain high performance with limited model capacity (e. g., 4-bit for both weights and activations).


Cross-view Semantic Segmentation for Sensing Surroundings

1 code implementation9 Jun 2019 Bowen Pan, Jiankai Sun, Ho Yin Tiga Leung, Alex Andonian, Bolei Zhou

Our further experiment on a LoCoBot robot shows that our model enables the surrounding sensing capability from 2D image input.

Domain Adaptation Semantic Segmentation

ATP: Directed Graph Embedding with Asymmetric Transitivity Preservation

1 code implementation2 Nov 2018 Jiankai Sun, Bortik Bandyopadhyay, Armin Bashizade, Jiongqian Liang, P. Sadayappan, Srinivasan Parthasarathy

Directed graphs have been widely used in Community Question Answering services (CQAs) to model asymmetric relationships among different types of nodes in CQA graphs, e. g., question, answer, user.

Community Question Answering Graph Embedding +1

ColdRoute: Effective Routing of Cold Questions in Stack Exchange Sites

1 code implementation2 Jul 2018 Jiankai Sun, Abhinav Vishnu, Aniket Chakrabarti, Charles Siegel, Srinivasan Parthasarathy

Using data from eight stack exchange sites, we are able to improve upon the routing metrics (Precision$@1$, Accuracy, MRR) over the state-of-the-art models such as semantic matching by $159. 5\%$,$31. 84\%$, and $40. 36\%$ for cold questions posted by existing askers, and $123. 1\%$, $27. 03\%$, and $34. 81\%$ for cold questions posted by new askers respectively.

QDEE: Question Difficulty and Expertise Estimation in Community Question Answering Sites

1 code implementation31 Mar 2018 Jiankai Sun, Sobhan Moosavi, Rajiv Ramnath, Srinivasan Parthasarathy

We also propose a model to route newly posted questions to appropriate users based on the difficulty level of the question and the expertise of the user.

Community Question Answering

Semi-supervised Embedding in Attributed Networks with Outliers

no code implementations23 Mar 2017 Jiongqian Liang, Peter Jacobs, Jiankai Sun, Srinivasan Parthasarathy

In this paper, we propose a novel framework, called Semi-supervised Embedding in Attributed Networks with Outliers (SEANO), to learn a low-dimensional vector representation that systematically captures the topological proximity, attribute affinity and label similarity of vertices in a partially labeled attributed network (PLAN).


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