Search Results for "corpus"

ARC-AGI is a benchmark dataset and experimental framework designed to evaluate and advance artificial general intelligence by testing systems on abstract reasoning tasks that require human-like problem-solving abilities. It consists of a curated set of tasks where models must infer patterns from input-output examples and apply those rules to new unseen cases, without relying on memorization or prior training data. The dataset is structured as grid-based puzzles, where each task requires...

honggfuzz is a general-purpose, high-performance fuzzer that mixes coverage feedback with practical crash triage to uncover memory-safety and logic bugs. It supports multiple fuzzing modes—stdin, file, and networking—so targets can be exercised the same way they run in production. Instrumentation via compiler hooks or hardware/perf counters guides mutations toward previously unseen edges, while persistent mode keeps the target process alive to amortize startup costs. The tool integrates...

The Big List of Naughty Strings is a community-maintained catalog of “gotcha” inputs that commonly break software, from unusual Unicode to SQL and script injection payloads. It exists so developers and QA engineers can easily test edge cases that normal test data would miss, such as zero-width characters, right-to-left marks, emojis, foreign alphabets, and long or malformed strings. By throwing these strings at forms, APIs, databases, and UIs, teams can discover encoding bugs, sanitizer...

...With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. For example, check out this example code for training on the Stanford Natural Language Inference (SNLI) Corpus. Now you've setup your pipeline, you may want to ensure that some functions run deterministically. Wrap any code that's random, with fork_rng and you'll be good to go. Now that you've computed your vocabulary, you may want to make use of pre-trained word vectors to set your embeddings.

...Concordance searcher - tool for translators who need their translations to "agree" with one standard. Concordia is a C++ library for fast text lookup in large corpora. It uses a RAM stored index, which takes up approximately 600MB of memory for a corpus of 2 million sentences. It is based on the idea of a suffix array, enhanced by the presence of other auxiliary data structures. The effects are stunning - Concordia is able to do simple substring lookup at the pace of 5000 queries per second (on personal PC) - a speed which can not be achieved by any other search library. Moreover, Concordia can perform its own "concordia search". ...

...Developers and scholars can build tools that query by author, era, keyword, or poetic form using the standardized data structure. Because the project is open, contributors improve metadata, correct text variants, and maintain consistency across classical collections. The corpus enables digital humanities, poetry apps, styling tools, and creative projects that intermix poems with translation, visualization, or musical settings.

RC-Data is a dataset generation framework created by Google DeepMind to produce large-scale reading comprehension question-answer pairs from CNN and Daily Mail news articles. The dataset, introduced in the 2015 paper “Teaching Machines to Read and Comprehend” (Hermann et al., NIPS 2015), was among the first large corpora designed to train and evaluate machine reading and comprehension models. The repository provides scripts for downloading archived CNN and Daily Mail articles from the...

Includes • Scripts for the program/ code developed • High level architecture diagrams • Install guides for developers • Links to end user documentation on the AusNC website Note: The BSD license applies to customised plug-ins, scripts and ingest programs developed by the AusNC project team. Additional open source, 3rd party software products used by the AusNC solution are referenced on our SF wiki space.

.... --- Highlights: --- org.knowceans.util: IndexQuickSort, TableList: apply order of one array/list to others +++ Vectors, ArrayUtils: array convenience +++ RandomSamplers, CokusRandom, ArmSampler, Densities: random sampling and distributions +++ Arguments: command line parser +++ StopWatch, Which, ExternalProcess: runtime stuff +++ ParallelFor: OpenMP workalike +++ PatternString, NamedGroupRegex: regex convenience --- org.knowceans.corpus: CorpusSearcher: full-text search engine +++ LabelNumCorpus: svmlight corpus storage and filtering +++ NIPS corpus with text, authors, labels and citations --- org.knowceans.map: InvertibleHashMultiMap, BijectiveHashMap: implement n:m and 1:1 relations. --- Other libs: knowceans-arms = port of the Adaptive Rejection Metropolis Sampler (ARMS) for arbitrary distributions +++ lda-j = port of lda-c, implementing Latent Dirichlet Allocation (LDA)

PyAnnotation is a Python Library to access and manipulate linguistically annotated corpus files. Supported file formats are Kura XML, Elan XML and Toolbox files. A Corpus Reader API is provided to support statistical analysis within the NLTK.