Papers Text Compression
“Text Compression” 태그가 달린 논문 43편 · 필터 해제
Neural Retrievers are Biased Towards LLM-Generated Content
Recently, the emergence of large language models (LLMs) has revolutionized the paradigm of information retrieval (IR) applications, especially in web search, by generating vast amounts of human-like texts on the Internet…
Information RetrievalRetrievalText CompressionSemantic Text Compression for Classification
We study semantic compression for text where meanings contained in the text are conveyed to a source decoder, e.g., for classification. The main motivator to move to such an approach of recovering the meaning without req…
ClassificationDecoderQuantizationSemantic Compression+5EntropyRank: Unsupervised Keyphrase Extraction via Side-Information Optimization for Language Model-based Text Compression
We propose an unsupervised method to extract keywords and keyphrases from texts based on a pre-trained language model (LM) and Shannon's information maximization. Specifically, our method extracts phrases having the high…
Keyphrase ExtractionLanguage ModelingLanguage ModellingText CompressionApproximating Human-Like Few-shot Learning with GPT-based Compression
In this work, we conceptualize the learning process as information compression. We seek to equip generative pre-trained models with human-like learning capabilities that enable data compression during inference. We prese…
Data CompressionFew-Shot LearningSemantic SimilaritySemantic Textual Similarity+4Gzip versus bag-of-words for text classification
The effectiveness of compression in text classification ('gzip') has recently garnered lots of attention. In this note we show that `bag-of-words' approaches can achieve similar or better results, and are more efficient.
Classificationtext-classificationText ClassificationText CompressionLLMZip: Lossless Text Compression using Large Language Models
We provide new estimates of an asymptotic upper bound on the entropy of English using the large language model LLaMA-7B as a predictor for the next token given a window of past tokens. This estimate is significantly smal…
Language ModelingLanguage ModellingLarge Language ModelText CompressionOptimal alphabet for single text compression
A text written using symbols from a given alphabet can be compressed using the Huffman code, which minimizes the length of the encoded text. It is necessary, however, to employ a text-specific codebook, i.e. the symbol-c…
Text CompressionContextualized Semantic Distance between Highly Overlapped Texts
Overlapping frequently occurs in paired texts in natural language processing tasks like text editing and semantic similarity evaluation. Better evaluation of the semantic distance between the overlapped sentences benefit…
Domain AdaptationLanguage ModelingLanguage ModellingMasked Language Modeling+7Text Compression-aided Transformer Encoding
Text encoding is one of the most important steps in Natural Language Processing (NLP). It has been done well by the self-attention mechanism in the current state-of-the-art Transformer encoder, which has brought about si…
Text CompressionMachine Translation with Unsupervised Length-Constraints
We have seen significant improvements in machine translation due to the usage of deep learning. While the improvements in translation quality are impressive, the encoder-decoder architecture enables many more possibiliti…
DecoderMachine TranslationSentenceSentence Compression+2Deleter: Leveraging BERT to Perform Unsupervised Successive Text Compression
Text compression has diverse applications such as Summarization, Reading Comprehension and Text Editing. However, almost all existing approaches require either hand-crafted features, syntactic labels or parallel data. Ev…
Language ModellingReading ComprehensionSentenceSentence Compression+1Data-efficient Neural Text Compression with Interactive Learning
Neural sequence-to-sequence models have been successfully applied to text compression. However, these models were trained on huge automatically induced parallel corpora, which are only available for a few domains and tas…
Active LearningHeadline GenerationSmall Data Image ClassificationText CompressionA study for Image compression using Re-Pair algorithm
The compression is an important topic in computer science which allows we to storage more amount of data on our data storage. There are several techniques to compress any file. In this manuscript will be described the mo…
Image CompressionText CompressionText Compression for Sentiment Analysis via Evolutionary Algorithms
Can textual data be compressed intelligently without losing accuracy in evaluating sentiment? In this study, we propose a novel evolutionary compression algorithm, PARSEC (PARts-of-Speech for sEntiment Compression), whic…
Data CompressionEvolutionary AlgorithmsGeneral ClassificationSentiment Analysis+2A Neural Network Approach for Mixing Language Models
The performance of Neural Network (NN)-based language models is steadily improving due to the emergence of new architectures, which are able to learn different natural language characteristics. This paper presents a nove…
Text CompressionLong-Short Range Context Neural Networks for Language Modeling
The goal of language modeling techniques is to capture the statistical and structural properties of natural languages from training corpora. This task typically involves the learning of short range dependencies, which ge…
Language ModelingLanguage ModellingText CompressionA Batch Noise Contrastive Estimation Approach for Training Large Vocabulary Language Models
Training large vocabulary Neural Network Language Models (NNLMs) is a difficult task due to the explicit requirement of the output layer normalization, which typically involves the evaluation of the full softmax function…
GPUText CompressionAuthorship Verification based on Compression-Models
Compression models represent an interesting approach for different classification tasks and have been used widely across many research fields. We adapt compression models to the field of authorship verification (AV), a b…
Authorship VerificationText ClassificationText CompressionSequential Recurrent Neural Networks for Language Modeling
Feedforward Neural Network (FNN)-based language models estimate the probability of the next word based on the history of the last N words, whereas Recurrent Neural Networks (RNN) perform the same task based only on the l…
Language ModelingLanguage ModellingText CompressionTuple-oriented Compression for Large-scale Mini-batch Stochastic Gradient Descent
Data compression is a popular technique for improving the efficiency of data processing workloads such as SQL queries and more recently, machine learning (ML) with classical batch gradient methods. But the efficacy of su…
Data CompressionOpen-Ended Question AnsweringText Compression