1 citations · 1 across the 8 of their papers we have counts for
8 papers
Unlocking Parallelism in Autoregressive Language Models via Speculative Decoding with Progressive Tree Drafting
Zipeng Gao, Zhi Zheng, Qingrong Xia +5
Speculative decoding has significantly accelerated Large Language Model (LLM) inference by alleviating memory-bound bottlenecks. However, traditional speculative decoding typically…
SmellBench: Towards Fine-Grained Evaluation of Code Agents on Refactoring Tasks
Fake Lin, Binbin Hu, Xi Zhu +6
Code Agents have achieved remarkable advances in recent years, exhibiting strong capabilities across a wide range of software engineering tasks. However, their misuse often produce…
Defending LLM-based Multi-Agent Systems Against Cooperative Attacks with Sentence-Level Rectification
Yaoyang Luo, Zhi Zheng, Ziwei Zhao +5
Recent years have witnessed the rapid development of Large Language Model-based Multi-Agent Systems (MAS), which excel at collaborative decision-making and complex problem-solving.…
LLM as GNN: Graph Vocabulary Learning for Text-Attributed Graph Foundation Models
Xi Zhu, Haochen Xue, Ziwei Zhao +7
Text-Attributed Graphs (TAGs), where each node is associated with text descriptions, are ubiquitous in real-world scenarios. They typically exhibit distinctive structure and domain…
Continuous Dynamic Modeling via Neural ODEs for Popularity Trajectory Prediction
Songbo Yang, Ziwei Zhao, Zihang Chen +3
Popularity prediction for information cascades has significant applications across various domains, including opinion monitoring and advertising recommendations. While most existin…
When Box Meets Graph Neural Network in Tag-aware Recommendation
Fake Lin, Ziwei Zhao, Xi Zhu +6
Last year has witnessed the re-flourishment of tag-aware recommender systems supported by the LLM-enriched tags. Unfortunately, though large efforts have been made, current solutio…
DynLLM: When Large Language Models Meet Dynamic Graph Recommendation
Ziwei Zhao, Fake Lin, Xi Zhu +6
Last year has witnessed the considerable interest of Large Language Models (LLMs) for their potential applications in recommender systems, which may mitigate the persistent issue o…
Knowledge Graph Pruning for Recommendation
Fake Lin, Xi Zhu, Ziwei Zhao +6
Recent years have witnessed the prosperity of knowledge graph based recommendation system (KGRS), which enriches the representation of users, items, and entities by structural know…