no code implementations • 1 Feb 2024 • Xinyue Chen, Pengyu Gao, Jiangjiang Song, Xiaoyang Tan
As language model agents leveraging external tools rapidly evolve, significant progress has been made in question-answering(QA) methodologies utilizing supplementary documents and the Retrieval-Augmented Generation (RAG) approach.
no code implementations • 24 Sep 2023 • Xinyue Chen, Jie Xu, Yazhou Ren, Xiaorong Pu, Ce Zhu, Xiaofeng Zhu, Zhifeng Hao, Lifang He
Second, the storage and usage of data from multiple clients in a distributed environment can lead to incompleteness of multi-view data.
1 code implementation • 2 Jun 2023 • Zhiqiu Lin, Xinyue Chen, Deepak Pathak, Pengchuan Zhang, Deva Ramanan
Our first observation is that they can be repurposed for discriminative tasks (such as image-text retrieval) by simply computing the match score of generating a particular text string given an image.
Ranked #45 on Visual Reasoning on Winoground
no code implementations • 4 May 2023 • Yun Tang, Anna Y. Sun, Hirofumi Inaguma, Xinyue Chen, Ning Dong, Xutai Ma, Paden D. Tomasello, Juan Pino
In order to leverage strengths of both modeling methods, we propose a solution by combining Transducer and Attention based Encoder-Decoder (TAED) for speech-to-text tasks.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +5
no code implementations • 13 Feb 2023 • Song Wu, Yazhou Ren, Aodi Yang, Xinyue Chen, Xiaorong Pu, Jing He, Liqiang Nie, Philip S. Yu
In this survey, we investigate the main contributions of deep learning applications using medical images in fighting against COVID-19 from the aspects of image classification, lesion localization, and severity quantification, and review different deep learning architectures and some image preprocessing techniques for achieving a preciser diagnosis.
no code implementations • 30 Sep 2022 • Burcu Sayin, Fabio Casati, Andrea Passerini, Jie Yang, Xinyue Chen
In this paper, we argue that the way we have been training and evaluating ML models has largely forgotten the fact that they are applied in an organization or societal context as they provide value to people.
no code implementations • 17 Nov 2021 • Yanqiu Wu, Xinyue Chen, Che Wang, Yiming Zhang, Keith W. Ross
In particular, Truncated Quantile Critics (TQC) achieves state-of-the-art asymptotic training performance on the MuJoCo benchmark with a distributional representation of critics; and Randomized Ensemble Double Q-Learning (REDQ) achieves high sample efficiency that is competitive with state-of-the-art model-based methods using a high update-to-data ratio and target randomization.
no code implementations • 14 Aug 2021 • ZiHao Zhou, Li Zhang, Xinyue Chen, Cheng-Xiang Wang, Jie Huang
In this paper, we conduct wireless channel measurements in indoor corridor scenarios at 2. 4, 5 and 6 GHz bands with bandwidth of 320 MHz.
1 code implementation • Remote Sensing 2021 • Jialang Xu, Chunbo Luo, Xinyue Chen, Shicai Wei, Yang Luo
In this paper we propose a novel multidirectional fusion and perception network for change detection in bi-temporal very-high-resolution remote sensing images.
Change Detection Change detection for remote sensing images +1
6 code implementations • ICLR 2021 • Xinyue Chen, Che Wang, Zijian Zhou, Keith Ross
Using a high Update-To-Data (UTD) ratio, model-based methods have recently achieved much higher sample efficiency than previous model-free methods for continuous-action DRL benchmarks.
2 code implementations • EMNLP 2020 • Yanlin Feng, Xinyue Chen, Bill Yuchen Lin, Peifeng Wang, Jun Yan, Xiang Ren
Existing work on augmenting question answering (QA) models with external knowledge (e. g., knowledge graphs) either struggle to model multi-hop relations efficiently, or lack transparency into the model's prediction rationale.
1 code implementation • NeurIPS 2020 • Xinyue Chen, Zijian Zhou, Zheng Wang, Che Wang, Yanqiu Wu, Keith Ross
There has recently been a surge in research in batch Deep Reinforcement Learning (DRL), which aims for learning a high-performing policy from a given dataset without additional interactions with the environment.
2 code implementations • IJCNLP 2019 • Bill Yuchen Lin, Xinyue Chen, Jamin Chen, Xiang Ren
Commonsense reasoning aims to empower machines with the human ability to make presumptions about ordinary situations in our daily life.
Ranked #29 on Common Sense Reasoning on CommonsenseQA (using extra training data)