https://github.com/chaofanma/fusioner
공식 코드Open-vocabulary Semantic Segmentation with Frozen Vision-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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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.
Open-vocabulary Semantic Segmentation with Frozen Vision-Language Models
Neural CRF Model for Sentence Alignment in Text Simplification
PMC-LLaMA: Towards Building Open-source Language Models for Medicine
Emergent Representations of Program Semantics in Language Models Trained on Programs
Enhancing Monocular 3D Scene Completion with Diffusion Model
Rethinking Vision-Language Model in Face Forensics: Multi-Modal Interpretable Forged Face Detector
Towards Automated Document Revision: Grammatical Error Correction, Fluency Edits, and Beyond
Remote Sensing Temporal Vision-Language Models: A Comprehensive Survey
Change-Agent: Towards Interactive Comprehensive Remote Sensing Change Interpretation and Analysis
Linguistic Minimal Pairs Elicit Linguistic Similarity in Large Language Models
HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression
Emergence of a High-Dimensional Abstraction Phase in Language Transformers
Bridging Information-Theoretic and Geometric Compression in Language Models
NuwaTS: a Foundation Model Mending Every Incomplete Time Series
Beyond Reactive Safety: Risk-Aware LLM Alignment via Long-Horizon Simulation
Enhancing Natural Language Representation with Large-Scale Out-of-Domain Commonsense
Compressing Neural Language Models by Sparse Word Representations
DynaPipe: Optimizing Multi-task Training through Dynamic Pipelines
On Softmax Direct Preference Optimization for Recommendation
SD-HuBERT: Sentence-Level Self-Distillation Induces Syllabic Organization in HuBERT
Large Language Model-informed ECG Dual Attention Network for Heart Failure Risk Prediction
Dialogue State Tracking with a Language Model using Schema-Driven Prompting
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.