https://github.com/plstory/ds2d
공식 코드DStruct2Design: Data and Benchmarks for Data Structure Driven Generative Floor Plan Design
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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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.
DStruct2Design: Data and Benchmarks for Data Structure Driven Generative Floor Plan Design
Nesterov Method for Asynchronous Pipeline Parallel Optimization
ECONET: Effective Continual Pretraining of Language Models for Event Temporal Reasoning
Regularized Training with Generated Datasets for Name-Only Transfer of Vision-Language Models
Polyglot Contextual Representations Improve Crosslingual Transfer
Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models
Exploring the Value of Pre-trained Language Models for Clinical Named Entity Recognition
LLM Self Defense: By Self Examination, LLMs Know They Are Being Tricked
NeuroCartography: Scalable Automatic Visual Summarization of Concepts in Deep Neural Networks
UniTable: Towards a Unified Framework for Table Recognition via Self-Supervised Pretraining
From Bytes to Borsch: Fine-Tuning Gemma and Mistral for the Ukrainian Language Representation
Fingerspelling PoseNet: Enhancing Fingerspelling Translation with Pose-Based Transformer Models
Generating Data with Text-to-Speech and Large-Language Models for Conversational Speech Recognition
EXMODD: An EXplanatory Multimodal Open-Domain Dialogue dataset
SAPA: Similarity-Aware Point Affiliation for Feature Upsampling
Robotouille: An Asynchronous Planning Benchmark for LLM Agents
GumbelSoft: Diversified Language Model Watermarking via the GumbelMax-trick
Exploring the Relationship between Alignment and Cross-lingual Transfer in Multilingual Transformers
PosterLLaVa: Constructing a Unified Multi-modal Layout Generator with LLM
Human in the Loop Adaptive Optimization for Improved Time Series Forecasting
AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ
DeTikZify: Synthesizing Graphics Programs for Scientific Figures and Sketches with TikZ
ByGPT5: End-to-End Style-conditioned Poetry Generation with Token-free Language Models
ChatGPT in the context of precision agriculture data analytics
Investigating Compositional Reasoning in Time Series Foundation Models
A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss
Can Compressed LLMs Truly Act? An Empirical Evaluation of Agentic Capabilities in LLM Compression
Pruner-Zero: Evolving Symbolic Pruning Metric from scratch for Large Language Models
Language Model Preference Evaluation with Multiple Weak Evaluators
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.