Search Results for author: Yichen Li

Found 24 papers, 8 papers with code

Large Language Model Bias Mitigation from the Perspective of Knowledge Editing

no code implementations15 May 2024 Ruizhe Chen, Yichen Li, Zikai Xiao, Zuozhu Liu

Existing debiasing methods inevitably make unreasonable or undesired predictions as they are designated and evaluated to achieve parity across different social groups but leave aside individual facts, resulting in modified existing knowledge.

Fairness knowledge editing +3

Face It Yourselves: An LLM-Based Two-Stage Strategy to Localize Configuration Errors via Logs

1 code implementation31 Mar 2024 Shiwen Shan, Yintong Huo, Yuxin Su, Yichen Li, Dan Li, Zibin Zheng

Based on the insights gained from the preliminary study, we propose an LLM-based two-stage strategy for end-users to localize the root-cause configuration properties based on logs.

FaultProfIT: Hierarchical Fault Profiling of Incident Tickets in Large-scale Cloud Systems

no code implementations27 Feb 2024 JunJie Huang, Jinyang Liu, Zhuangbin Chen, Zhihan Jiang, Yichen Li, Jiazhen Gu, Cong Feng, Zengyin Yang, Yongqiang Yang, Michael R. Lyu

To date, FaultProfIT has analyzed 10, 000+ incidents from 30+ cloud services, successfully revealing several fault trends that have informed system improvements.

Contrastive Learning

Enhancing LLM-Based Coding Tools through Native Integration of IDE-Derived Static Context

no code implementations6 Feb 2024 Yichen Li, Yun Peng, Yintong Huo, Michael R. Lyu

We conducted preliminary experiments to validate the performance of IDECoder and observed that this synergy represents a promising trend for future exploration.

Code Completion

An Empirical Study on Large Language Models in Accuracy and Robustness under Chinese Industrial Scenarios

no code implementations27 Jan 2024 Zongjie Li, Wenying Qiu, Pingchuan Ma, Yichen Li, You Li, Sijia He, Baozheng Jiang, Shuai Wang, Weixi Gu

In this paper, we present a comprehensive empirical study on the accuracy and robustness of LLMs in the context of the Chinese industrial production area.

Ensemble-based Interactive Imitation Learning

no code implementations28 Dec 2023 Yichen Li, Chicheng Zhang

We study interactive imitation learning, where a learner interactively queries a demonstrating expert for action annotations, aiming to learn a policy that has performance competitive with the expert, using as few annotations as possible.

Continuous Control Imitation Learning

Efficient Human-AI Coordination via Preparatory Language-based Convention

no code implementations1 Nov 2023 Cong Guan, Lichao Zhang, Chunpeng Fan, Yichen Li, Feng Chen, Lihe Li, Yunjia Tian, Lei Yuan, Yang Yu

Developing intelligent agents capable of seamless coordination with humans is a critical step towards achieving artificial general intelligence.

Language Modelling Large Language Model

Siamese-DETR for Generic Multi-Object Tracking

no code implementations27 Oct 2023 Qiankun Liu, Yichen Li, Yuqi Jiang, Ying Fu

Recently, Open-Vocabulary MOT (OVMOT) and Generic MOT (GMOT) are proposed to track interested objects beyond pre-defined categories with the given text prompt and template image.

Autonomous Driving Language Modelling +3

ASAP: Automated Sequence Planning for Complex Robotic Assembly with Physical Feasibility

no code implementations29 Sep 2023 Yunsheng Tian, Karl D. D. Willis, Bassel Al Omari, Jieliang Luo, Pingchuan Ma, Yichen Li, Farhad Javid, Edward Gu, Joshua Jacob, Shinjiro Sueda, Hui Li, Sachin Chitta, Wojciech Matusik

The automated assembly of complex products requires a system that can automatically plan a physically feasible sequence of actions for assembling many parts together.

Missing-modality Enabled Multi-modal Fusion Architecture for Medical Data

no code implementations27 Sep 2023 Muyu Wang, Shiyu Fan, Yichen Li, Hui Chen

This study aimed to develop an efficient multi-modal fusion architecture for medical data that was robust to missing modalities and further improved the performance on disease diagnosis. X-ray chest radiographs for the image modality, radiology reports for the text modality, and structured value data for the tabular data modality were fused in this study.


Improving the Transferability of Adversarial Samples by Path-Augmented Method

1 code implementation CVPR 2023 Jianping Zhang, Jen-tse Huang, Wenxuan Wang, Yichen Li, Weibin Wu, Xiaosen Wang, Yuxin Su, Michael R. Lyu

However, such methods selected the image augmentation path heuristically and may augment images that are semantics-inconsistent with the target images, which harms the transferability of the generated adversarial samples.

Image Augmentation

DaFKD: Domain-Aware Federated Knowledge Distillation

no code implementations CVPR 2023 Haozhao Wang, Yichen Li, Wenchao Xu, Ruixuan Li, Yufeng Zhan, Zhigang Zeng

In this paper, we propose a new perspective that treats the local data in each client as a specific domain and design a novel domain knowledge aware federated distillation method, dubbed DaFKD, that can discern the importance of each model to the distillation sample, and thus is able to optimize the ensemble of soft predictions from diverse models.

Knowledge Distillation

On Efficient Online Imitation Learning via Classification

no code implementations26 Sep 2022 Yichen Li, Chicheng Zhang

We make the following contributions: (1) we show that in the $\textbf{COIL}$ problem, any proper online learning algorithm cannot guarantee a sublinear regret in general; (2) we propose $\textbf{Logger}$, an improper online learning algorithmic framework, that reduces $\textbf{COIL}$ to online linear optimization, by utilizing a new definition of mixed policy class; (3) we design two oracle-efficient algorithms within the $\textbf{Logger}$ framework that enjoy different sample and interaction round complexity tradeoffs, and conduct finite-sample analyses to show their improvements over naive behavior cloning; (4) we show that under the standard complexity-theoretic assumptions, efficient dynamic regret minimization is infeasible in the $\textbf{Logger}$ framework.

Classification Imitation Learning

Towards Making Deep Learning-based Vulnerability Detectors Robust

1 code implementation2 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.

Network Architecture Search for Domain Adaptation

no code implementations13 Aug 2020 Yichen Li, Xingchao Peng

Deep networks have been used to learn transferable representations for domain adaptation.

Domain Adaptation Image Classification +1

Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation

1 code implementation ECCV 2020 Xingchao Peng, Yichen Li, Kate Saenko

Extensive experiments are conducted to demonstrate the power of our new datasets in benchmarking state-of-the-art multi-source domain adaptation methods, as well as the advantage of our proposed model.

Benchmarking Disentanglement +2

Learning Domain Adaptive Features with Unlabeled Domain Bridges

no code implementations10 Dec 2019 Yichen Li, Xingchao Peng

Secondly, we propose the Prototypical Adversarial Domain Adaptation (PADA) model which utilizes unlabeled bridge domains to align feature distribution between source and target with a large discrepancy.

Image-to-Image Translation Translation +1

Revisiting Image-Language Networks for Open-ended Phrase Detection

3 code implementations17 Nov 2018 Bryan A. Plummer, Kevin J. Shih, Yichen Li, Ke Xu, Svetlana Lazebnik, Stan Sclaroff, Kate Saenko

Most existing work that grounds natural language phrases in images starts with the assumption that the phrase in question is relevant to the image.

object-detection Object Detection +1

A 20-Liter Test Stand with Gas Purification for Liquid Argon Research

1 code implementation4 Feb 2016 Yichen Li, Craig Thorn, Wei Tang, Jyoti Joshi, Xin Qian, Milind Diwan, Steve Kettell, William Morse, Triveni Rao, James Stewart, Thomas Tsang, Lige Zhang

We describe the design of a 20-liter test stand constructed to study fundamental properties of liquid argon (LAr).

Instrumentation and Detectors High Energy Physics - Experiment

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