Search Results for author: Yichen Liu

Found 30 papers, 10 papers with code

ManuSearch: Democratizing Deep Search in Large Language Models with a Transparent and Open Multi-Agent Framework

1 code implementation23 May 2025 Lisheng Huang, Yichen Liu, Jinhao Jiang, Rongxiang Zhang, Jiahao Yan, Junyi Li, Wayne Xin Zhao

Recent advances in web-augmented large language models (LLMs) have exhibited strong performance in complex reasoning tasks, yet these capabilities are mostly locked in proprietary systems with opaque architectures.

Dynamic Regularized CBDT: Variance-Calibrated Causal Boosting for Interpretable Heterogeneous Treatment Effects

no code implementations18 Apr 2025 Yichen Liu

Heterogeneous treatment effect estimation in high-stakes applications demands models that simultaneously optimize precision, interpretability, and calibration.

Heterogeneous Treatment Effect Estimation

Deep Learning for Time Series Forecasting: A Survey

no code implementations13 Mar 2025 Xiangjie Kong, Zhenghao Chen, Weiyao Liu, Kaili Ning, Lechao Zhang, Syauqie Muhammad Marier, Yichen Liu, Yuhao Chen, Feng Xia

However, existing surveys have not provided a unified summary of the wide range of model architectures in this field, nor have they given detailed summaries of works in feature extraction and datasets.

Deep Learning Survey +2

Music Genre Classification: Ensemble Learning with Subcomponents-level Attention

no code implementations20 Dec 2024 Yichen Liu, Abhijit Dasgupta, Qiwei He

Music Genre Classification is one of the most popular topics in the fields of Music Information Retrieval (MIR) and digital signal processing.

Ensemble Learning Genre classification +3

UniMLVG: Unified Framework for Multi-view Long Video Generation with Comprehensive Control Capabilities for Autonomous Driving

1 code implementation6 Dec 2024 Rui Chen, Zehuan Wu, Yichen Liu, Yuxin Guo, Jingcheng Ni, Haifeng Xia, Siyu Xia

The creation of diverse and realistic driving scenarios has become essential to enhance perception and planning capabilities of the autonomous driving system.

Autonomous Driving Diversity +1

LIFBench: Evaluating the Instruction Following Performance and Stability of Large Language Models in Long-Context Scenarios

1 code implementation11 Nov 2024 Xiaodong Wu, Minhao Wang, Yichen Liu, Xiaoming Shi, He Yan, Xiangju Lu, Junmin Zhu, Wei zhang

As Large Language Models (LLMs) evolve in natural language processing (NLP), their ability to stably follow instructions in long-context inputs has become critical for real-world applications.

Instruction Following

Mobility-LLM: Learning Visiting Intentions and Travel Preferences from Human Mobility Data with Large Language Models

1 code implementation29 Oct 2024 Letian Gong, Yan Lin, Xinyue Zhang, Yiwen Lu, Xuedi Han, Yichen Liu, Shengnan Guo, Youfang Lin, Huaiyu Wan

Drawing inspiration from the exceptional semantic understanding and contextual information processing capabilities of large language models (LLMs) across various domains, we present Mobility-LLM, a novel framework that leverages LLMs to analyze check-in sequences for multiple tasks.

Optimized Biomedical Question-Answering Services with LLM and Multi-BERT Integration

no code implementations11 Oct 2024 Cheng Qian, Xianglong Shi, Shanshan Yao, Yichen Liu, Fengming Zhou, Zishu Zhang, Junaid Akram, Ali Braytee, Ali Anaissi

We present a refined approach to biomedical question-answering (QA) services by integrating large language models (LLMs) with Multi-BERT configurations.

Decision Making Question Answering

Advancing Humanoid Locomotion: Mastering Challenging Terrains with Denoising World Model Learning

1 code implementation26 Aug 2024 Xinyang Gu, Yen-Jen Wang, Xiang Zhu, Chengming Shi, Yanjiang Guo, Yichen Liu, Jianyu Chen

In this work, we introduce Denoising World Model Learning (DWL), an end-to-end reinforcement learning framework for humanoid locomotion control, which demonstrates the world's first humanoid robot to master real-world challenging terrains such as snowy and inclined land in the wild, up and down stairs, and extremely uneven terrains.

Denoising reinforcement-learning +1

PTrajM: Efficient and Semantic-rich Trajectory Learning with Pretrained Trajectory-Mamba

no code implementations9 Aug 2024 Yan Lin, Yichen Liu, Zeyu Zhou, Haomin Wen, Erwen Zheng, Shengnan Guo, Youfang Lin, Huaiyu Wan

To better utilize vehicle trajectories, it is essential to develop a trajectory learning approach that can effectively and efficiently extract rich semantic information, including movement behavior and travel purposes, to support accurate downstream applications.

Mamba

Multi-Garment Customized Model Generation

no code implementations9 Aug 2024 Yichen Liu, Penghui Du, Yi Liu Quanwei Zhang

This paper introduces Multi-Garment Customized Model Generation, a unified framework based on Latent Diffusion Models (LDMs) aimed at addressing the unexplored task of synthesizing images with free combinations of multiple pieces of clothing.

model

VP-LLM: Text-Driven 3D Volume Completion with Large Language Models through Patchification

no code implementations8 Jun 2024 Jianmeng Liu, Yichen Liu, Yuyao Zhang, Zeyuan Meng, Yu-Wing Tai, Chi-Keung Tang

Recent conditional 3D completion works have mainly relied on CLIP or BERT to encode textual information, which cannot support complex instruction.

Neural Radiance Field in Autonomous Driving: A Survey

no code implementations22 Apr 2024 Lei He, Leheng Li, Wenchao Sun, Zeyu Han, Yichen Liu, Sifa Zheng, Jianqiang Wang, Keqiang Li

To the best of our knowledge, this is the first survey specifically focused on the applications of NeRF in the Autonomous Driving domain.

3D Reconstruction Autonomous Driving +4

DepthMOT: Depth Cues Lead to a Strong Multi-Object Tracker

1 code implementation8 Apr 2024 Jiapeng Wu, Yichen Liu

Inspired by this, even though the bounding boxes of objects are close on the camera plane, we can differentiate them in the depth dimension, thereby establishing a 3D perception of the objects.

Camera Pose Estimation Multi-Object Tracking +2

DiffYOLO: Object Detection for Anti-Noise via YOLO and Diffusion Models

no code implementations3 Jan 2024 Yichen Liu, Huajian Zhang, Daqing Gao

Object detection models represented by YOLO series have been widely used and have achieved great results on the high quality datasets, but not all the working conditions are ideal.

Denoising object-detection +1

SANeRF-HQ: Segment Anything for NeRF in High Quality

no code implementations CVPR 2024 Yichen Liu, Benran Hu, Chi-Keung Tang, Yu-Wing Tai

Recently, the Segment Anything Model (SAM) has showcased remarkable capabilities of zero-shot segmentation, while NeRF (Neural Radiance Fields) has gained popularity as a method for various 3D problems beyond novel view synthesis.

NeRF Novel View Synthesis +5

centroIDA: Cross-Domain Class Discrepancy Minimization Based on Accumulative Class-Centroids for Imbalanced Domain Adaptation

no code implementations21 Aug 2023 Xiaona Sun, Zhenyu Wu, Yichen Liu, Saier Hu, ZhiQiang Zhan, Yang Ji

Unsupervised Domain Adaptation (UDA) approaches address the covariate shift problem by minimizing the distribution discrepancy between the source and target domains, assuming that the label distribution is invariant across domains.

Robust classification Unsupervised Domain Adaptation

Building a digital twin of EDFA: a grey-box modeling approach

no code implementations13 Jul 2023 Yichen Liu, Xiaomin Liu, Yihao Zhang, Meng Cai, Mengfan Fu, Xueying Zhong, Lilin Yi, Weisheng Hu, Qunbi Zhuge

To enable intelligent and self-driving optical networks, high-accuracy physical layer models are required.

On Uni-Modal Feature Learning in Supervised Multi-Modal Learning

1 code implementation2 May 2023 Chenzhuang Du, Jiaye Teng, Tingle Li, Yichen Liu, Tianyuan Yuan, Yue Wang, Yang Yuan, Hang Zhao

We abstract the features (i. e. learned representations) of multi-modal data into 1) uni-modal features, which can be learned from uni-modal training, and 2) paired features, which can only be learned from cross-modal interactions.

Instance Neural Radiance Field

1 code implementation ICCV 2023 Yichen Liu, Benran Hu, Junkai Huang, Yu-Wing Tai, Chi-Keung Tang

This paper presents one of the first learning-based NeRF 3D instance segmentation pipelines, dubbed as {\bf \inerflong}, or \inerf.

3D Instance Segmentation NeRF +2

ONeRF: Unsupervised 3D Object Segmentation from Multiple Views

no code implementations22 Nov 2022 Shengnan Liang, Yichen Liu, Shangzhe Wu, Yu-Wing Tai, Chi-Keung Tang

We present ONeRF, a method that automatically segments and reconstructs object instances in 3D from multi-view RGB images without any additional manual annotations.

3D scene Editing Object +1

NeRF-RPN: A general framework for object detection in NeRFs

2 code implementations CVPR 2023 Benran Hu, Junkai Huang, Yichen Liu, Yu-Wing Tai, Chi-Keung Tang

This paper presents the first significant object detection framework, NeRF-RPN, which directly operates on NeRF.

NeRF object-detection +1

A Grey-box Launch-profile Aware Model for C+L Band Raman Amplification

no code implementations24 Jun 2022 Yihao Zhang, Xiaomin Liu, Yichen Liu, Lilin Yi, Weisheng Hu, Qunbi Zhuge

Based on the physical features of Raman amplification, we propose a three-step modelling scheme based on neural networks (NN) and linear regression.

regression

Confidence-aware Self-Semantic Distillation on Knowledge Graph Embedding

no code implementations7 Jun 2022 Yichen Liu, Jiawei Chen, Defang Chen, Zhehui Zhou, Yan Feng, Can Wang

Knowledge Graph Embedding (KGE), which projects entities and relations into continuous vector spaces, has garnered significant attention.

Knowledge Graph Embedding Knowledge Graphs +3

Learning Visual Styles from Audio-Visual Associations

no code implementations10 May 2022 Tingle Li, Yichen Liu, Andrew Owens, Hang Zhao

Our model learns to manipulate the texture of a scene to match a sound, a problem we term audio-driven image stylization.

Image Stylization

Native Chinese Reader: A Dataset Towards Native-Level Chinese Machine Reading Comprehension

no code implementations13 Dec 2021 Shusheng Xu, Yichen Liu, Xiaoyu Yi, Siyuan Zhou, Huizi Li, Yi Wu

We present Native Chinese Reader (NCR), a new machine reading comprehension (MRC) dataset with particularly long articles in both modern and classical Chinese.

Articles Common Sense Reasoning +1

Improving Multi-Modal Learning with Uni-Modal Teachers

no code implementations21 Jun 2021 Chenzhuang Du, Tingle Li, Yichen Liu, Zixin Wen, Tianyu Hua, Yue Wang, Hang Zhao

We name this problem Modality Failure, and hypothesize that the imbalance of modalities and the implicit bias of common objectives in fusion method prevent encoders of each modality from sufficient feature learning.

Image Segmentation Semantic Segmentation

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