6 papers
DrKGC: Dynamic Subgraph Retrieval-Augmented LLMs for Knowledge Graph Completion across General and Biomedical Domains
Yongkang Xiao, Sinian Zhang, Yi Dai +4
Knowledge graph completion (KGC) aims to predict missing triples in knowledge graphs (KGs) by leveraging existing triples and textual information. Recently, generative large langua…
Private Queries with Sigma-Counting
Jun Gao, Jie Ding
Many data applications involve counting queries, where a client specifies a feasible range of variables and a database returns the corresponding item counts. A program that produce…
SlimRAG: Retrieval without Graphs via Entity-Aware Context Selection
Jiale Zhang, Jiaxiang Chen, Zhucong Li +5
Retrieval-Augmented Generation (RAG) enhances language models by incorporating external knowledge at inference time. However, graph-based RAG systems often suffer from structural o…
Safety Aware Task Planning via Large Language Models in Robotics
Azal Ahmad Khan, Michael Andrev, Muhammad Ali Murtaza +5
The integration of large language models (LLMs) into robotic task planning has unlocked better reasoning capabilities for complex, long-horizon workflows. However, ensuring safety…
Probe Pruning: Accelerating LLMs through Dynamic Pruning via Model-Probing
Qi Le, Enmao Diao, Ziyan Wang +4
We introduce Probe Pruning (PP), a novel framework for online, dynamic, structured pruning of Large Language Models (LLMs) applied in a batch-wise manner. PP leverages the insight…
MAP: Multi-Human-Value Alignment Palette
Xinran Wang, Qi Le, Ammar Ahmed +5
Ensuring that generative AI systems align with human values is essential but challenging, especially when considering multiple human values and their potential trade-offs. Since hu…