Search Results for author: Xufang Luo

Found 19 papers, 3 papers with code

LLM-ABR: Designing Adaptive Bitrate Algorithms via Large Language Models

no code implementations2 Apr 2024 Zhiyuan He, Aashish Gottipati, Lili Qiu, Francis Y. Yan, Xufang Luo, Kenuo Xu, Yuqing Yang

We present LLM-ABR, the first system that utilizes the generative capabilities of large language models (LLMs) to autonomously design adaptive bitrate (ABR) algorithms tailored for diverse network characteristics.

reinforcement-learning

LLM-RadJudge: Achieving Radiologist-Level Evaluation for X-Ray Report Generation

no code implementations1 Apr 2024 Zilong Wang, Xufang Luo, Xinyang Jiang, Dongsheng Li, Lili Qiu

This study proposes a novel evaluation framework using large language models (LLMs) to compare radiology reports for assessment.

Knowledge Distillation

LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression

1 code implementation19 Mar 2024 Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, Menglin Xia, Xufang Luo, Jue Zhang, QIngwei Lin, Victor Rühle, Yuqing Yang, Chin-Yew Lin, H. Vicky Zhao, Lili Qiu, Dongmei Zhang

The challenge is that information entropy may be a suboptimal compression metric: (i) it only leverages unidirectional context and may fail to capture all essential information needed for prompt compression; (ii) it is not aligned with the prompt compression objective.

GSM8K Language Modelling +3

LSPT: Long-term Spatial Prompt Tuning for Visual Representation Learning

no code implementations27 Feb 2024 Shentong Mo, Yansen Wang, Xufang Luo, Dongsheng Li

Visual Prompt Tuning (VPT) techniques have gained prominence for their capacity to adapt pre-trained Vision Transformers (ViTs) to downstream visual tasks using specialized learnable tokens termed as prompts.

Representation Learning Visual Prompt Tuning

Toward Open-ended Embodied Tasks Solving

no code implementations10 Dec 2023 William Wei Wang, Dongqi Han, Xufang Luo, Yifei Shen, Charles Ling, Boyu Wang, Dongsheng Li

Empowering embodied agents, such as robots, with Artificial Intelligence (AI) has become increasingly important in recent years.

Unified Medical Image Pre-training in Language-Guided Common Semantic Space

no code implementations24 Nov 2023 Xiaoxuan He, Yifan Yang, Xinyang Jiang, Xufang Luo, Haoji Hu, Siyun Zhao, Dongsheng Li, Yuqing Yang, Lili Qiu

To overcome the aforementioned challenges, we propose an Unified Medical Image Pre-training framework, namely UniMedI, which utilizes diagnostic reports as common semantic space to create unified representations for diverse modalities of medical images (especially for 2D and 3D images).

AdaMedGraph: Adaboosting Graph Neural Networks for Personalized Medicine

no code implementations24 Nov 2023 Jie Lian, Xufang Luo, Caihua Shan, Dongqi Han, Varut Vardhanabhuti, Dongsheng Li

However, selecting the appropriate edge feature to define patient similarity and construct the graph is challenging, given that each patient is depicted by high-dimensional features from diverse sources.

LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression

1 code implementation10 Oct 2023 Huiqiang Jiang, Qianhui Wu, Xufang Luo, Dongsheng Li, Chin-Yew Lin, Yuqing Yang, Lili Qiu

Inspired by these findings, we propose LongLLMLingua for prompt compression towards improving LLMs' perception of the key information to simultaneously address the three challenges.

Code Completion Few-Shot Learning

Is Risk-Sensitive Reinforcement Learning Properly Resolved?

no code implementations2 Jul 2023 Ruiwen Zhou, Minghuan Liu, Kan Ren, Xufang Luo, Weinan Zhang, Dongsheng Li

Due to the nature of risk management in learning applicable policies, risk-sensitive reinforcement learning (RSRL) has been realized as an important direction.

Distributional Reinforcement Learning Management +2

Protecting the Future: Neonatal Seizure Detection with Spatial-Temporal Modeling

no code implementations2 Jul 2023 Ziyue Li, Yuchen Fang, You Li, Kan Ren, Yansen Wang, Xufang Luo, Juanyong Duan, Congrui Huang, Dongsheng Li, Lili Qiu

A timely detection of seizures for newborn infants with electroencephalogram (EEG) has been a common yet life-saving practice in the Neonatal Intensive Care Unit (NICU).

EEG Seizure Detection

Adaptive Policy Learning for Offline-to-Online Reinforcement Learning

no code implementations14 Mar 2023 Han Zheng, Xufang Luo, Pengfei Wei, Xuan Song, Dongsheng Li, Jing Jiang

In this paper, we consider an offline-to-online setting where the agent is first learned from the offline dataset and then trained online, and propose a framework called Adaptive Policy Learning for effectively taking advantage of offline and online data.

Continuous Control Offline RL +2

Bootstrapped Transformer for Offline Reinforcement Learning

no code implementations17 Jun 2022 Kerong Wang, Hanye Zhao, Xufang Luo, Kan Ren, Weinan Zhang, Dongsheng Li

Offline reinforcement learning (RL) aims at learning policies from previously collected static trajectory data without interacting with the real environment.

Offline RL reinforcement-learning +1

Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble

no code implementations19 May 2022 Zhengyu Yang, Kan Ren, Xufang Luo, Minghuan Liu, Weiqing Liu, Jiang Bian, Weinan Zhang, Dongsheng Li

Considering the great performance of ensemble methods on both accuracy and generalization in supervised learning (SL), we design a robust and applicable method named Ensemble Proximal Policy Optimization (EPPO), which learns ensemble policies in an end-to-end manner.

reinforcement-learning Reinforcement Learning (RL)

VRL3: A Data-Driven Framework for Visual Deep Reinforcement Learning

1 code implementation17 Feb 2022 Che Wang, Xufang Luo, Keith Ross, Dongsheng Li

We propose VRL3, a powerful data-driven framework with a simple design for solving challenging visual deep reinforcement learning (DRL) tasks.

Offline RL reinforcement-learning +1

Deep Ensemble Policy Learning

no code implementations29 Sep 2021 Zhengyu Yang, Kan Ren, Xufang Luo, Weiqing Liu, Jiang Bian, Weinan Zhang, Dongsheng Li

Ensemble learning, which can consistently improve the prediction performance in supervised learning, has drawn increasing attentions in reinforcement learning (RL).

Ensemble Learning Reinforcement Learning (RL)

Adaptive Q-learning for Interaction-Limited Reinforcement Learning

no code implementations29 Sep 2021 Han Zheng, Xufang Luo, Pengfei Wei, Xuan Song, Dongsheng Li, Jing Jiang

Specifically, we explicitly consider the difference between the online and offline data and apply an adaptive update scheme accordingly, i. e., a pessimistic update strategy for the offline dataset and a greedy or no pessimistic update scheme for the online dataset.

Offline RL Q-Learning +2

P-BN: Towards Effective Batch Normalization in the Path Space

no code implementations25 Sep 2019 Xufang Luo, Qi Meng, Wei Chen, Tie-Yan Liu

Hence, some new algorithms that conduct optimizations directly in the path space (the path space is proven to be PSI) were developed, such as Stochastic Gradient Descent (SGD) in the path space, and it was shown that SGD in the path space is superior to that in the weight space.

Expressiveness in Deep Reinforcement Learning

no code implementations27 Sep 2018 Xufang Luo, Qi Meng, Di He, Wei Chen, Yunhong Wang, Tie-Yan Liu

Based on our observations, we formally define expressiveness of the state extractor as the rank of the matrix composed by representations.

Atari Games reinforcement-learning +2

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