Non-linear effects in long-haul, high-speed optical fiber systems significantly hinder channel capacity.
1 code implementation • 30 Oct 2023 • Heather Lent, Kushal Tatariya, Raj Dabre, Yiyi Chen, Marcell Fekete, Esther Ploeger, Li Zhou, Hans Erik Heje, Diptesh Kanojia, Paul Belony, Marcel Bollmann, Loïc Grobol, Miryam de Lhoneux, Daniel Hershcovich, Michel DeGraff, Anders Søgaard, Johannes Bjerva
Creoles represent an under-explored and marginalized group of languages, with few available resources for NLP research.
Conclusion: Despite growing attention to bias in healthcare AI, research using EHR data on this topic is still limited.
We introduce a new task involving the translation and cultural adaptation of recipes between Chinese and English-speaking cuisines.
Recently, transformer models emerged as a promising avenue to enhance LDCT image quality.
In the field of natural language understanding, the intersection of neural models and graph meaning representations (GMRs) remains a compelling area of research.
The increasing ubiquity of language technology necessitates a shift towards considering cultural diversity in the machine learning realm, particularly for subjective tasks that rely heavily on cultural nuances, such as Offensive Language Detection (OLD).
In this paper, we propose the CARLG model, which consists of two modules: Contextual Clues Aggregation (CCA) and Role-based Latent Information Guidance (RLIG), effectively leveraging contextual clues and role correlations for improving document-level EAE.
no code implementations • 26 Aug 2023 • Jianqiang Xia, Dianxi Shi, Ke Song, Linna Song, Xiaolei Wang, Songchang Jin, Li Zhou, Yu Cheng, Lei Jin, Zheng Zhu, Jianan Li, Gang Wang, Junliang Xing, Jian Zhao
With this structure, the network can extract fusion features of the template and search region under the mutual interaction of modalities.
The utilization of social media in epidemic surveillance has been well established.
The confounding factors, which are non-sensitive variables but manifest systematic differences, can significantly affect fairness evaluation.
The recent release of ChatGPT has garnered widespread recognition for its exceptional ability to generate human-like responses in dialogue.
Such a separated framework overlooks the link between visual grounding and tracking, which is that the natural language descriptions provide global semantic cues for localizing the target for both two steps.
Ranked #3 on Visual Tracking on TNL2K
Time-trend analysis revealed that Hydroxychloroquine and Ivermectin received much more discussion than Molnupiravir and Remdesivir, particularly during COVID-19 surges.
GraphEye is originated from the observation that the code property graph of a non-vulnerable function naturally differs from the code property graph of a vulnerable function with the same functionality.
In DPGNN, we utilize node features to construct a feature graph, and perform node representations learning based on the original topology graph and the constructed feature graph simultaneously, which conduce to capture the structural neighborhood information and the feature-related information.
Motivated by suggested question generation in conversational news recommendation systems, we propose a model for generating question-answer pairs (QA pairs) with self-contained, summary-centric questions and length-constrained, article-summarizing answers.
Therefore, in this paper, we focus on predicting users' intention destinations in online travel platforms.
With the development of the 5G and Internet of Things, amounts of wireless devices need to share the limited spectrum resources.
Machine learning (ML) has been widely used for efficient resource allocation (RA) in wireless networks.
1 code implementation • 2 Feb 2021 • Sensong An, Bowen Zheng, Mikhail Y. Shalaginov, Hong Tang, Hang Li, Li Zhou, Yunxi Dong, Mohammad Haerinia, Anuradha Murthy Agarwal, Clara Rivero-Baleine, Myungkoo Kang, Kathleen A. Richardson, Tian Gu, Juejun Hu, Clayton Fowler, Hualiang Zhang
Metasurfaces have provided a novel and promising platform for the realization of compact and large-scale optical devices.
Starting from the essence of the music, the article constructs a music-rule-identifying algorithm through extracting modes, which will identify the stability of the mode of machine-generated music, to judge whether it is artificial intelligent.
In this paper, we propose a novel adversarial inverse reinforcement learning algorithm to learn a language-conditioned policy and reward function.
This paper presents XiaoiceSing, a high-quality singing voice synthesis system which employs an integrated network for spectrum, F0 and duration modeling.
1 code implementation • 1 Jan 2020 • Sensong An, Bowen Zheng, Mikhail Y. Shalaginov, Hong Tang, Hang Li, Li Zhou, Jun Ding, Anuradha Murthy Agarwal, Clara Rivero-Baleine, Myungkoo Kang, Kathleen A. Richardson, Tian Gu, Juejun Hu, Clayton Fowler, Hualiang Zhang
Metasurfaces have shown promising potentials in shaping optical wavefronts while remaining compact compared to bulky geometric optics devices.
In this paper, we propose Proq, a runtime assertion scheme for testing and debugging quantum programs on a quantum computer.
Multi-domain dialogue state tracking (DST) is a critical component for conversational AI systems.
Ranked #9 on Multi-domain Dialogue State Tracking on MULTIWOZ 2.0
An extreme learning machine (ELM)-based heterogeneous domain adaptation (HDA) algorithm is proposed for the classification of remote sensing images.
Metasurfaces have enabled precise electromagnetic wave manipulation with strong potential to obtain unprecedented functionalities and multifunctional behavior in flat optical devices.
no code implementations • 8 Jun 2019 • Sensong An, Clayton Fowler, Bowen Zheng, Mikhail Y. Shalaginov, Hong Tang, Hang Li, Li Zhou, Jun Ding, Anuradha Murthy Agarwal, Clara Rivero-Baleine, Kathleen A. Richardson, Tian Gu, Juejun Hu, Hualiang Zhang
Metasurfaces have become a promising means for manipulating optical wavefronts in flat and high-performance optical devices.
The evaluator defines a learnable information preserving metric between original video and summary video and "supervises" the selector to identify the most informative frames to form the summary video.
Ranked #7 on Unsupervised Video Summarization on TvSum
Pharmaceutical targeting is one of key inputs for making sales and marketing strategy planning.
At the same time, the sequential nature of input/weight processing of RNNs mitigates one of the downsides of DWM, which is the linear (rather than constant) data access time. RNNFast is very efficient and highly scalable, with flexible mapping of logical neurons to RNN hardware blocks.
Detecting the relations among objects, such as "cat on sofa" and "person ride horse", is a crucial task in image understanding, and beneficial to bridging the semantic gap between images and natural language.
Despite the noticeable progress in perceptual tasks like detection, instance segmentation and human parsing, computers still perform unsatisfactorily on visually understanding humans in crowded scenes, such as group behavior analysis, person re-identification and autonomous driving, etc.
Ranked #1 on Multi-Human Parsing on PASCAL-Part
Learning a goal-oriented dialog policy is generally performed offline with supervised learning algorithms or online with reinforcement learning (RL).
The second part performs matching cost calculation, matching cost aggregation and disparity calculation to estimate the initial disparity using shared features.
We consider both the benefit of leveraging a set of learned latent user classes for new users, and how we can learn such latent classes from prior users.