semantic relationships
In AI, semantic relationships refer to the connections and meanings that exist between concepts or entities. Understanding these relationships is critical for natural language processing tasks, knowledge representation, and information retrieval.
- ChunkKV: Semantic-Preserving KV Cache Compression for Efficient Long-Context LLM Inference
- Demystifying Language Model Forgetting with Low-rank Example Associations
- GoT: Unleashing Reasoning Capability of MLLM for Visual Generation and Editing
- Mitigating Semantic Collapse in Partially Relevant Video Retrieval
- Object-Centric Representation Learning for Enhanced 3D Semantic Scene Graph Prediction
- Quality-Driven Curation of Remote Sensing Vision-Language Data via Learned Scoring Models
- RankMatch: A Novel Approach to Semi-Supervised Label Distribution Learning Leveraging Rank Correlation between Labels
- Towards A Generalist Code Embedding Model Based On Massive Data Synthesis
- Vgent: Graph-based Retrieval-Reasoning-Augmented Generation For Long Video Understanding