collaborators

5 papers

cs.DB2025

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…

cs.IR2025

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…

cs.AI2025

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…

cs.RO2025

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…

cs.CL2025

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…