https://github.com/alanbaade/SyllableLM
공식 코드SyllableLM: Learning Coarse Semantic Units for Speech Language Models
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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
SyllableLM: Learning Coarse Semantic Units for Speech Language Models
Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences
Circuit Stability Characterizes Language Model Generalization
Contrastive Novelty-Augmented Learning: Anticipating Outliers with Large Language Models
A Tool for Facilitating OCR Postediting in Historical Documents
Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs
A Statistical Investigation of Long Memory in Language and Music
A Simple and Effective $L_2$ Norm-Based Strategy for KV Cache Compression
Towards Goal-oriented Prompt Engineering for Large Language Models: A Survey
Rewriting the Code: A Simple Method for Large Language Model Augmented Code Search
Converting the Point of View of Messages Spoken to Virtual Assistants
DinoSR: Self-Distillation and Online Clustering for Self-supervised Speech Representation Learning
MoRE-LLM: Mixture of Rule Experts Guided by a Large Language Model
Efficient Hierarchical Domain Adaptation for Pretrained Language Models
Reusing a Pretrained Language Model on Languages with Limited Corpora for Unsupervised NMT
An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language Models
Representation Learning of Daily Movement Data Using Text Encoders
Reasoning Large Language Model Errors Arise from Hallucinating Critical Problem Features
Neuron to Graph: Interpreting Language Model Neurons at Scale
A Simple Baseline for Predicting Events with Auto-Regressive Tabular Transformers
DziriBERT: a Pre-trained Language Model for the Algerian Dialect
Controlling Vision-Language Models for Multi-Task Image Restoration
Distillation and Refinement of Reasoning in Small Language Models for Document Re-ranking
Ditto: A Simple and Efficient Approach to Improve Sentence Embeddings
Exploring Key Point Analysis with Pairwise Generation and Graph Partitioning
SeqGPT: An Out-of-the-box Large Language Model for Open Domain Sequence Understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.