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In this paper, we propose a novel design for AI-native goal-oriented communications, exploiting transformer neural networks under dynamic inference constraints on bandwidth and computation. Transformers have become the standard architecture…

Information Theory · Computer Science 2024-05-07 Alessio Devoto , Simone Petruzzi , Jary Pomponi , Paolo Di Lorenzo , Simone Scardapane

The global popularity of microblogs has led to an increasing accumulation of large volumes of text data on microblogging platforms such as Twitter. These corpora are untapped resources to understand social expressions on diverse subjects.…

Information Retrieval · Computer Science 2018-11-15 Tharindu Rukshan Bandaragoda , Daswin De Silva , Damminda Alahakoon

We present a novel summarization framework for reviews of products and services by selecting informative and concise text segments from the reviews. Our method consists of two major steps. First, we identify five frequently occurring…

Information Retrieval · Computer Science 2012-11-26 Trung V. Nguyen , Alice H. Oh

Current research has explored how Generative AI can support the brainstorming process for content creators, but a gap remains in exploring support-tools for the pre-writing process. Specifically, our research is focused on supporting users…

Human-Computer Interaction · Computer Science 2024-06-19 Grace Li , Tao Long , Lydia B. Chilton

This paper explores a variant of automatic headline generation methods, where a generated headline is required to include a given phrase such as a company or a product name. Previous methods using Transformer-based models generate a…

Computation and Language · Computer Science 2021-09-16 Kosuke Yamada , Yuta Hitomi , Hideaki Tamori , Ryohei Sasano , Naoaki Okazaki , Kentaro Inui , Koichi Takeda

One of the major sources of trending news, events and opinion in the current age is micro blogging. Twitter, being one of them, is extensively used to mine data about public responses and event updates. This paper intends to propose methods…

Social and Information Networks · Computer Science 2015-06-22 Rishabh Jain , Abhishek B. S. , Satvik Jagannath

In this paper, we transform tag recommendation into a word-based text generation problem and introduce a sequence-to-sequence model. The model inherits the advantages of LSTM-based encoder for sequential modeling and attention-based decoder…

Computation and Language · Computer Science 2019-12-03 Xuewen Shi , Heyan Huang , Shuyang Zhao , Ping Jian , Yi-Kun Tang

Scene text segmentation aims at cropping texts from scene images, which is usually used to help generative models edit or remove texts. The existing text segmentation methods tend to involve various text-related supervisions for better…

Computer Vision and Pattern Recognition · Computer Science 2024-07-25 Haiyang Yu , Teng Fu , Bin Li , Xiangyang Xue

Twitter is a popular social network platform where users can interact and post texts of up to 280 characters called tweets. Hashtags, hyperlinked words in tweets, have increasingly become crucial for tweet retrieval and search. Using…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-01-29 Vibhuti Gupta , Rattikorn Hewett

Short-text classification, like all data science, struggles to achieve high performance using limited data. As a solution, a short sentence may be expanded with new and relevant feature words to form an artificially enlarged dataset, and…

Computation and Language · Computer Science 2019-09-18 Duncan Cameron-Steinke

Generative models reliant on sequential autoregression have been at the forefront of language generation for an extensive period, particularly following the introduction of widely acclaimed transformers. Despite its excellent performance,…

Computation and Language · Computer Science 2024-06-21 Yaguang Li , Xin Chen

We present a new topic model that generates documents by sampling a topic for one whole sentence at a time, and generating the words in the sentence using an RNN decoder that is conditioned on the topic of the sentence. We argue that this…

Computation and Language · Computer Science 2017-08-03 Ramesh Nallapati , Igor Melnyk , Abhishek Kumar , Bowen Zhou

Current deep networks are very data-hungry and benefit from training on largescale datasets, which are often time-consuming to collect and annotate. By contrast, synthetic data can be generated infinitely using generative models such as…

Computer Vision and Pattern Recognition · Computer Science 2023-10-11 Weijia Wu , Yuzhong Zhao , Hao Chen , Yuchao Gu , Rui Zhao , Yefei He , Hong Zhou , Mike Zheng Shou , Chunhua Shen

Argument Mining(AM) aims to uncover the argumentative structures within a text. Previous methods require several subtasks, such as span identification, component classification, and relation classification. Consequently, these methods need…

Computation and Language · Computer Science 2026-03-26 Masayuki Kawarada , Tsutomu Hirao , Wataru Uchida , Masaaki Nagata

Semantic segmentation has been widely investigated in the community, in which the state of the art techniques are based on supervised models. Those models have reported unprecedented performance at the cost of requiring a large set of high…

Computer Vision and Pattern Recognition · Computer Science 2022-01-11 Rihuan Ke , Angelica Aviles-Rivero , Saurabh Pandey , Saikumar Reddy , Carola-Bibiane Schönlieb

Automatic speech transcripts are often delivered as unstructured word streams that impede readability and repurposing. We recast paragraph segmentation as the missing structuring step and fill three gaps at the intersection of speech…

Computation and Language · Computer Science 2026-04-10 Fabian Retkowski , Alexander Waibel

On-line handwritten character segmentation is often associated with handwriting recognition and even though recognition models include mechanisms to locate relevant positions during the recognition process, it is typically insufficient to…

Computer Vision and Pattern Recognition · Computer Science 2023-09-07 Michael Jungo , Beat Wolf , Andrii Maksai , Claudiu Musat , Andreas Fischer

Structured sentences are important expressions in human writings and dialogues. Previous works on neural text generation fused semantic and structural information by encoding the entire sentence into a mixed hidden representation. However,…

Computation and Language · Computer Science 2020-05-11 Xing Wu , Dongjun Wei , Liangjun Zang , Jizhong Han , Songlin Hu

A combination of a neural network with rule firing information from a rule-based system is used to generate segment durations for a text-to-speech system. The system shows a slight improvement in performance over a neural network system…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Gerald Corrigan , Noel Massey , Orhan Karaali

Microblogs such as Twitter represent a powerful source of information. Part of this information can be aggregated beyond the level of individual posts. Some of this aggregated information is referring to events that could or should be acted…

Computation and Language · Computer Science 2020-08-04 Ali Hürriyetoğlu