https://github.com/templex98/mova
공식 코드MoVA: Adapting Mixture of Vision Experts to Multimodal Context
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
A knowledge graph is a structured representation of information that organizes data into nodes (entities) and edges (relationships) to show how different pieces of knowledge are interconnected. It enables enhanced data integration, search, and inference by modeling the relationships between concepts and entities in a graph format.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
MoVA: Adapting Mixture of Vision Experts to Multimodal Context
Sentient Agent as a Judge: Evaluating Higher-Order Social Cognition in Large Language Models
SEED-Story: Multimodal Long Story Generation with Large Language Model
Constructing and Evaluating Declarative RAG Pipelines in PyTerrier
OptiMUS: Optimization Modeling Using MIP Solvers and large language models
Adaptations of AI models for querying the LandMatrix database in natural language
Rot-Pro: Modeling Transitivity by Projection in Knowledge Graph Embedding
Extending Transductive Knowledge Graph Embedding Models for Inductive Logical Relational Inference
Enhancing Biomedical Lay Summarisation with External Knowledge Graphs
Enhancing Speech-to-Speech Dialogue Modeling with End-to-End Retrieval-Augmented Generation
Leveraging Domain Knowledge for Inclusive and Bias-aware Humanitarian Response Entry Classification
FinBen: A Holistic Financial Benchmark for Large Language Models
Pneuma: Leveraging LLMs for Tabular Data Representation and Retrieval in an End-to-End System
Mechanistic Interpretability in the Presence of Architectural Obfuscation
Learning What Reinforcement Learning Can't: Interleaved Online Fine-Tuning for Hardest Questions
Improving Interpersonal Communication by Simulating Audiences with Language Models
Simple and Interpretable Probabilistic Classifiers for Knowledge Graphs
Agentic Reasoning: Reasoning LLMs with Tools for the Deep Research
AspectMMKG: A Multi-modal Knowledge Graph with Aspect-aware Entities
Autonomous Agents for Collaborative Task under Information Asymmetry
EXIT: Context-Aware Extractive Compression for Enhancing Retrieval-Augmented Generation
IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation
From Distributional to Overton Pluralism: Investigating Large Language Model Alignment
Can LLM Watermarks Robustly Prevent Unauthorized Knowledge Distillation?
JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.