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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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/sacmehta/delight
공식 코드https://github.com/safeailab/eagle
공식 코드EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty
https://github.com/saffronh/ccai
공식 코드Collective Constitutional AI: Aligning a Language Model with Public Input
https://github.com/safolab-wisc/fiubench
공식 코드Benchmarking Vision Language Model Unlearning via Fictitious Facial Identity Dataset
https://github.com/sagorbrur/bangla-bert
공식 코드Emotion Classification in a Resource Constrained Language Using Transformer-based Approach
https://github.com/sai990323/tallrec
공식 코드https://github.com/saic-fi/bayesian-prompt-learning
공식 코드Bayesian Prompt Learning for Image-Language Model Generalization
https://github.com/sail-sg/agent-smith
공식 코드Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast
https://github.com/sail-sg/regmix
공식 코드RegMix: Data Mixture as Regression for Language Model Pre-training
https://github.com/sail-sg/sailor-llm
공식 코드https://github.com/sail-sg/sdft
공식 코드Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning
https://github.com/sailxuovo/cc-riddle
공식 코드CC-Riddle: A Question Answering Dataset of Chinese Character Riddles
https://github.com/saitejautpala/dp_prompt
공식 코드Locally Differentially Private Document Generation Using Zero Shot Prompting
https://github.com/sajaddarabi/TAPER
공식 코드https://github.com/sajaddarabi/TAPER-EHR
공식 코드https://github.com/sakanaai/ai-scientist
공식 코드The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery
https://github.com/sakharamg/kitlm
공식 코드KITLM: Domain-Specific Knowledge InTegration into Language Models for Question Answering
https://github.com/salehiac/languagegroundedqd
공식 코드Integrating LLMs and Decision Transformers for Language Grounded Generative Quality-Diversity
https://github.com/salesforce/CodeGen
공식 코드CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis
https://github.com/salesforce/DialogStudio
공식 코드DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI
https://github.com/salesforce/adversarial-polyglots
공식 코드Code-Mixing on Sesame Street: Dawn of the Adversarial Polyglots
https://github.com/salesforce/awd-lstm-lm
공식 코드https://github.com/salesforce/codegen2
공식 코드CodeGen2: Lessons for Training LLMs on Programming and Natural Languages
https://github.com/salesforce/diversesumm
공식 코드https://github.com/salesforce/ebm_calibration_nlu
공식 코드Joint Energy-based Model Training for Better Calibrated Natural Language Understanding Models
https://github.com/salesforce/fewshot_absa
공식 코드A Generative Language Model for Few-shot Aspect-Based Sentiment Analysis
https://github.com/salesforce/jaxformer
공식 코드CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis
https://github.com/salesforce/lavis
공식 코드https://github.com/salesforce/qvr-simpledlm
공식 코드Value Retrieval with Arbitrary Queries for Form-like Documents
https://github.com/salesforce/simpletod
공식 코드https://github.com/salesforce/ulip
공식 코드ULIP: Learning a Unified Representation of Language, Images, and Point Clouds for 3D Understanding
https://github.com/salesforceairesearch/answer-engine-eval
공식 코드Search Engines in an AI Era: The False Promise of Factual and Verifiable Source-Cited Responses
https://github.com/salesforceairesearch/faitheval
공식 코드https://github.com/salt-nlp/chain-of-thought-bias
공식 코드On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning
https://github.com/salt-nlp/culturebank
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.