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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
SARA: Selective and Adaptive Retrieval-augmented Generation with Context Compression
LeAD: The LLM Enhanced Planning System Converged with End-to-end Autonomous Driving
TalkFashion: Intelligent Virtual Try-On Assistant Based on Multimodal Large Language Model
GeoMag: A Vision-Language Model for Pixel-level Fine-Grained Remote Sensing Image Parsing
MusiScene: Leveraging MU-LLaMA for Scene Imagination and Enhanced Video Background Music Generation
Evolution without Large Models: Training Language Model with Task Principles
PrefixAgent: An LLM-Powered Design Framework for Efficient Prefix Adder Optimization
Differential Mamba
Evaluating Morphological Alignment of Tokenizers in 70 Languages
A Systematic Analysis of Hybrid Linear Attention
PRIME: Large Language Model Personalization with Cognitive Memory and Thought Processes
Inaugural MOASEI Competition at AAMAS'2025: A Technical Report
Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model
MambaFusion: Height-Fidelity Dense Global Fusion for Multi-modal 3D Object Detection
FA: Forced Prompt Learning of Vision-Language Models for Out-of-Distribution Detection
Transforming Calabi-Yau Constructions: Generating New Calabi-Yau Manifolds with Transformers
DeSTA2.5-Audio: Toward General-Purpose Large Audio Language Model with Self-Generated Cross-Modal Alignment
OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering
Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows
Auto-TA: Towards Scalable Automated Thematic Analysis (TA) via Multi-Agent Large Language Models with Reinforcement Learning
LineRetriever: Planning-Aware Observation Reduction for Web Agents
A Large Language Model-Empowered Agent for Reliable and Robust Structural Analysis
Beyond Reactive Safety: Risk-Aware LLM Alignment via Long-Horizon Simulation
SharpZO: Hybrid Sharpness-Aware Vision Language Model Prompt Tuning via Forward-Only Passes
V2X-REALM: Vision-Language Model-Based Robust End-to-End Cooperative Autonomous Driving with Adaptive Long-Tail Modeling
DALR: Dual-level Alignment Learning for Multimodal Sentence Representation Learning
Prompt-Guided Turn-Taking Prediction
Enhancing Automatic Term Extraction with Large Language Models via Syntactic Retrieval
World-aware Planning Narratives Enhance Large Vision-Language Model Planner
Detecting Referring Expressions in Visually Grounded Dialogue with Autoregressive Language Models
Data Efficacy for Language Model Training
mTSBench: Benchmarking Multivariate Time Series Anomaly Detection and Model Selection at Scale
AgentStealth: Reinforcing Large Language Model for Anonymizing User-generated Text
Can "consciousness" be observed from large language model (LLM) internal states? Dissecting LLM representations obtained from Theory of Mind test with Integrated Information Theory and Span Representation analysis
Large Language Model Agent for Modular Task Execution in Drug Discovery
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.