Language Modelling
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A language model is a model of natural language. Language models are useful for a variety of tasks, including speech recognition, machine translation, natural language generation (generating more human-like text), optical character recognition, route optimization, handwriting recognition, grammar induction, and information retrieval.
Large language models (LLMs), currently their most advanced form, are predominantly based on transformers trained on larger datasets (frequently using words scraped from the public internet). They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.
Source: Wikipedia
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/veronica320/wikihow-gosc
공식 코드https://github.com/veronicium/codebenchgen
공식 코드CodeBenchGen: Creating Scalable Execution-based Code Generation Benchmarks
https://github.com/versusdebias/versusdebias
공식 코드https://github.com/vevake/DomainAware_DST
공식 코드Domain-Aware Dialogue State Tracker for Multi-Domain Dialogue Systems
https://github.com/vgthengane/climb3d
공식 코드CLIMB-3D: Continual Learning for Imbalanced 3D Instance Segmentation
https://github.com/vhellendoorn/code-lms
공식 코드https://github.com/via-research/vtrain
공식 코드https://github.com/vicentvankor/sun-shine
공식 코드https://github.com/vicgalle/configurable-safety-tuning
공식 코드Configurable Safety Tuning of Language Models with Synthetic Preference Data
https://github.com/vicgalle/meta-self-critique
공식 코드MetaSC: Test-Time Safety Specification Optimization for Language Models
https://github.com/vicgalle/zero-shot-reward-models
공식 코드ZYN: Zero-Shot Reward Models with Yes-No Questions for RLAIF
https://github.com/vicky-wil/monitor
공식 코드https://github.com/vicmak/ProofSeer
공식 코드https://github.com/victor-wang-902/surealm
공식 코드https://github.com/victor7246/transject
공식 코드Manifold-Preserving Transformers are Effective for Short-Long Range Encoding
https://github.com/victordibia/neuralqa
공식 코드https://github.com/victorwz/valm
공식 코드https://github.com/vid-koci/bert-commonsense
공식 코드https://github.com/vida-nyu/satori-assistance
공식 코드Satori: Towards Proactive AR Assistant with Belief-Desire-Intention User Modeling
https://github.com/vidhishanair/factedit
공식 코드https://github.com/vidit09/domaingen
공식 코드CLIP the Gap: A Single Domain Generalization Approach for Object Detection
https://github.com/viethoang1512/pga
공식 코드Enhancing Domain Adaptation through Prompt Gradient Alignment
https://github.com/viking-sudo-rm/StackNN
공식 코드https://github.com/viking-sudo-rm/formal-language-understanding
공식 코드Entailment Semantics Can Be Extracted from an Ideal Language Model
https://github.com/viking-sudo-rm/industrial-stacknns
공식 코드https://github.com/vila-lab/gblm-pruner
공식 코드Beyond Size: How Gradients Shape Pruning Decisions in Large Language Models
https://github.com/vimalabs/VIMABench
공식 코드https://github.com/vinairesearch/phoatis_disfluency
공식 코드From Disfluency Detection to Intent Detection and Slot Filling
https://github.com/vinairesearch/recgpt
공식 코드RecGPT: Generative Pre-training for Text-based Recommendation
https://github.com/vinairesearch/unibridge
공식 코드UniBridge: A Unified Approach to Cross-Lingual Transfer Learning for Low-Resource Languages
https://github.com/vinid/prodb
공식 코드BERT Goes Shopping: Comparing Distributional Models for Product Representations
https://github.com/vinusankars/reliability-of-ai-text-detectors
공식 코드https://github.com/vipulgupta1011/calm
공식 코드CALM : A Multi-task Benchmark for Comprehensive Assessment of Language Model Bias
https://github.com/virajprabhu/lance
공식 코드LANCE: Stress-testing Visual Models by Generating Language-guided Counterfactual Images
https://github.com/virallab/turkishbertweet
공식 코드TurkishBERTweet: Fast and Reliable Large Language Model for Social Media Analysis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.