7 papers
Mapping Text to Multiplex Graph: Prompt Compression as Lévy Walk-Guided Graph Pruning
Yaxin Gao, Yao Lu, Jinhong Deng +7
Existing prompt compression methods treat text as flat token sequences, failing to capture the distributed nature of important information, which is often spread across multiple lo…
Rethinking LLM Ensembling from the Perspective of Mixture Models
Jiale Fu, Yuchu Jiang, Peijun Wu +3
Model ensembling is a well-established technique for improving the performance of machine learning models. Conventionally, this involves averaging the output distributions of multi…
A Two-Dimensional Framework for AI Agent Design Patterns: Cognitive Function and Execution Topology
Jia Huang, Joey Tianyi Zhou
Existing frameworks for LLM-based agent architectures describe systems from a single perspective: industry guides (Anthropic, Google, LangChain) focus on execution topology -- how…
From Compression to Accountability: Harmless Copyright Protection for Dataset Distillation
Yan Liang, Ziyuan Yang, Mengyu Sun +2
Large-scale datasets have been a key driving force behind the rapid progress of deep learning, but their storage, computational, and energy costs have become increasingly prohibiti…
Plan in Sandbox, Navigate in Open Worlds: Learning Physics-Grounded Abstracted Experience for Embodied Navigation
Zhixuan Shen, Jiawei Du, Ziyu Guo +5
Vision-Language Models (VLMs) have demonstrated exceptional general reasoning capabilities. However, their performance in embodied navigation remains hindered by a scarcity of alig…
SQLAgent: Learning to Explore Before Generating as a Data Engineer
Wenjia Jiang, Yiwei Wang, Boyan Han +2
Large Language Models have recently shown impressive capabilities in reasoning and code generation, making them promising tools for natural language interfaces to relational databa…
A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment
Kun Wang, Guibin Zhang, Zhenhong Zhou +100
The remarkable success of Large Language Models (LLMs) has illuminated a promising pathway toward achieving Artificial General Intelligence for both academic and industrial communi…