Search Results for "alignment" - Page 5
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Showing 125 open source projects for "alignment"
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XLM (Cross-lingual Language Model)
PyTorch original implementation of Cross-lingual Language Model
...It popularized objectives like Masked Language Modeling (MLM) across many languages and Translation Language Modeling (TLM) that jointly trains on parallel sentence pairs to tighten cross-lingual alignment. Using a shared subword vocabulary, XLM learns language-agnostic features that work well for classification and sequence labeling tasks such as XNLI, NER, and POS without target-language supervision. The repository provides preprocessing pipelines, training code, and fine-tuning scripts so you can reproduce benchmark results or adapt models to your own multilingual corpora. ... -
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Synonyms
Chinese synonyms, chat robot, intelligent question and answer toolkit
Chinese Synonyms for natural language processing and understanding. Better Chinese synonyms, chatbot, intelligent question and answer toolkit. synonymsCan be used for many tasks in natural language understanding, text alignment, recommendation algorithms, similarity calculation, semantic shifting, keyword extraction, concept extraction, automatic summarization, search engines, etc. Print synonyms in a friendly way for easy debugging. "Synonyms Cilin" was compiled by Mei Jiaju and others in 1983, and now widely used is "Synonyms Cilin Extended Edition" maintained by the Social Computing and Information Retrieval Research Center of Harbin Institute of Technology. ... -
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CMU Sphinx
Speech Recognition Toolkit
Thank you for visiting! ----> Maintenance and improvement work has MOVED to https://cmusphinx.github.io/ Please go there for the most recent software and documentation. <---- CMUSphinx is a speaker-independent large vocabulary continuous speech recognizer released under BSD style license. It is also a collection of open source tools and resources that allows researchers and developers to build speech recognition systems. -
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MUSE
A library for Multilingual Unsupervised or Supervised word Embeddings
MUSE is a framework for learning multilingual word embeddings that live in a shared space, enabling bilingual lexicon induction, cross-lingual retrieval, and zero-shot transfer. It supports both supervised alignment with seed dictionaries and unsupervised alignment that starts without parallel data by using adversarial initialization followed by Procrustes refinement. The code can align pre-trained monolingual embeddings (such as fastText) across dozens of languages and provides standardized evaluation scripts and dictionaries. By mapping languages into a common vector space, MUSE makes it straightforward to build cross-lingual applications where resources are scarce for some languages. ... -
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Tacotron-2
DeepMind's Tacotron-2 Tensorflow implementation
...It includes directory layouts and logging directories for multiple datasets such as LJSpeech and M-AILABS en_US/en_UK, making it easier to adapt to new English corpora. Separate log trees track mel-spectrograms, attention plots, evaluation audio, and vocoder outputs, so you can inspect how alignment and audio quality evolve over time. -
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face-recognition.js
Simple Node.js package for robust face detection and face recognition
...Developers can compare unknown faces with stored examples and receive ranked predictions with distance values. The package also includes five-point and 68-point facial landmark predictors for alignment and analysis. Synchronous and Promise-based asynchronous methods support different application designs, while OpenCV integration enables additional image processing. OpenBLAS can improve CPU performance when the native dependency is compiled with it. The project is now considered obsolete by its author, who recommends face-api.js for equivalent browser and Node.js functionality. -
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PyTom
http://www.sciencedirect.com/science/article/pii/S1047847711003492
PyTom is a toolbox developed for interpreting cryo electron tomography data. All steps from reconstruction, localization, alignment and classification are covered with standard and improved methods. Please sign up to our mailing list to keep up with the most recent updates and versions. -
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2D Statistical Models. Building: shape model, texture model and concatenated appearance model; Fitting: 1D profile ASM, 2D profile ASM, direct local texture constrained(LTC) ASM, basic AAM, ICIA AAM, IAIA AAM, etc.
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Portable Robotics Eye Vergence Control
Eye movements control portable on different robotic stereo heads
This project provides a software module for the control of the binocular coordination of a robotic stereo head, based on a bio-inspired algorithm. The project is now available for the iCub platform to work on YARP [https://github.com/stino78/vergence-control/][1] The algorithm works on the top of a distributed representation of binocular disparity supplied by a population of binocular energy-model neural units. The project allows a robust control and adaptive binocular coordination... -
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logmap-matcher
LogMap: An Ontology Alignment and Alignment Repair System
LogMap is a highly scalable ontology matching system with ‘built-in’ reasoning and inconsistency repair capabilities. LogMap extract mappings between classes, properties and instances. To the best of our knowledge, LogMap is one of the few matching systems that: 1. can efficiently match semantically rich ontologies containing tens (and even hundreds) of thousands of classes, 2. incorporates sophisticated reasoning and repair techniques to minimise the number of logical... -
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PolyRec
Unistroke gesture recognizer
...More technical details on PolyRec can be found in the following scientific paper: V Fuccella, G. Costagliola; Unistroke Gesture Recognition Through Polyline Approximation and Alignment; in Proceedings of CHI 2015; pp. 3351-3354 http://dl.acm.org/citation.cfm?id=2702 -
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OnAGUI - Ontology Alignment GUI
Software to help automatic or manual realisation of ontologi alignment
This project has moved to https://github.com/lmazuel/onagui - OnAGUI (Ontology Alignment Graphical User Interface) is a project of alignment helper and viewer. You can edit ontology (SKOS, OWL) and edit alignment between concept of these ontologies. In addition, you can make automatic discovery of alignment, using different kind of algorithm. This work was initiated by Jean Charlet (http://www.limics.fr/index.php/annuaire), designed and developped by Laurent Mazuel on a post-doctoral project. ... -
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S-Match
S-Match is a semantic matching framework.
...S-Match contains implementations of the semantic matching, minimal semantic matching and structure preserving semantic matching algorithms. S-Match applies as a solution in many fields, including: information integration, ontology evolution and alignment, peer-to-peer information sharing, digital libraries integration, web service composition, agent communication, and query answering on the web. S-Match is extendable to host new algorithms. -
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jaivox
Speech recognition application builder and library
Java library and tools to create open source speech recognition applications. Generates dialogs for conversational interfaces. Works with a popular open source speech recognition library. -
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FineSplice
Enhanced splice junction detection and estimation from RNA-Seq data
FineSplice is a Python wrapper to TopHat2 geared towards a reliable identification of expressed exon junctions from RNA-Seq data, at enhanced detection precision with small loss in sensitivity. Following alignment with TopHat2 using known transcript annotations, FineSplice takes as input the resulting BAM file and outputs a confident set of expressed splice junctions with the corresponding read counts. Potential false positives arising from spurious alignments are filtered out via a semi-supervised anomaly detection strategy based on logistic regression. ... -
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MapPSO is a tool for Ontology Alignment, which uses Discrete Particle Swarm Optimisation. A particle swarm is used to search for the optimal alignment. The algorithm is massively parallel and adapts naturally on parallel architectures.
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KADMOS provides a lightweight API for alignment of OWL 2 ontologies. It is based on the OWL API v3.
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Sanchay is a collection of tools and APIs for language researchers. It has some implementations of NLP algorithms, some flexible APIs, several user friendly annotation interfaces and Sanchay Query Language for language resources.
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Tifftool is a high-performance tool to clean scanned documents in preparation for onscreen display or for OCR. Features include skew correction, orientation correction, despeckle, page alignment, split pages and batch processing.
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mms-300m-1130-forced-aligner
CTC-based forced aligner for audio-text in 158 languages
mms-300m-1130-forced-aligner is a multilingual forced alignment model based on Meta’s MMS-300M wav2vec2 checkpoint, adapted for Hugging Face’s Transformers library. It supports forced alignment between audio and corresponding text across 158 languages, offering broad multilingual coverage. The model enables accurate word- or phoneme-level timestamping using Connectionist Temporal Classification (CTC) emissions. -
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Qwen3-Next
Qwen3-Next: 80B instruct LLM with ultra-long context up to 1M tokens
...Multi-Token Prediction (MTP) boosts both training and inference, while stability optimizations such as weight-decayed and zero-centered layernorm ensure robustness. Benchmarks show it performs comparably to larger models like Qwen3-235B on reasoning, coding, multilingual, and alignment tasks while requiring only a fraction of the training cost. -
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Hermes 4
Hermes 4 FP8: hybrid reasoning Llama-3.1-405B model by Nous Research
Hermes 4 405B FP8 is a cutting-edge large language model developed by Nous Research, built on Llama-3.1-405B and optimized for frontier reasoning and alignment. It introduces a hybrid reasoning mode with explicit <think> segments, enabling the model to deliberate deeply when needed and switch to faster responses when desired. Post-training improvements include a vastly expanded corpus with ~60B tokens, boosting performance across math, code, STEM, logic, creativity, and structured outputs. ... -
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Qwen2.5-VL-7B-Instruct
Multimodal 7B model for image, video, and text understanding tasks
Qwen2.5-VL-7B-Instruct is a multimodal vision-language model developed by the Qwen team, designed to handle text, images, and long videos with high precision. Fine-tuned from Qwen2.5-VL, this 7-billion-parameter model can interpret visual content such as charts, documents, and user interfaces, as well as recognize common objects. It supports complex tasks like visual question answering, localization with bounding boxes, and structured output generation from documents. The model is also... -
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Llama-3.2-1B-Instruct
Instruction-tuned 1.2B LLM for multilingual text generation by Meta
Llama-3.2-1B-Instruct is Meta’s multilingual, instruction-tuned large language model with 1.24 billion parameters, optimized for dialogue, summarization, and retrieval tasks. It builds upon the Llama 3.1 architecture and incorporates fine-tuning techniques like SFT, DPO, and quantization-aware training for improved alignment, efficiency, and safety. The model supports eight primary languages (including English, Spanish, Hindi, and Thai) and was trained on a curated mix of publicly available online data, with a December 2023 knowledge cutoff. Llama-3.2-1B is lightweight enough for deployment on constrained devices like smartphones, using formats like SpinQuant and QLoRA to reduce model size and latency. ... -
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fashion-clip
CLIP model fine-tuned for zero-shot fashion product classification
FashionCLIP is a domain-adapted CLIP model fine-tuned specifically for the fashion industry, enabling zero-shot classification and retrieval of fashion products. Developed by Patrick John Chia and collaborators, it builds on the CLIP ViT-B/32 architecture and was trained on over 800K image-text pairs from the Farfetch dataset. The model learns to align product images and descriptive text using contrastive learning, enabling it to perform well across various fashion-related tasks without...
