most citedBridging Context Gaps: Leveraging Coreference Resolution for Long Contextual Understanding

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL20242 cited

Bridging Context Gaps: Leveraging Coreference Resolution for Long Contextual Understanding

Yanming Liu, Xinyue Peng, Jiannan Cao +6

Large language models (LLMs) have shown remarkable capabilities in natural language processing; however, they still face difficulties when tasked with understanding lengthy context…

cs.CR2024

DP-MemArc: Differential Privacy Transfer Learning for Memory Efficient Language Models

Yanming Liu, Xinyue Peng, Yuwei Zhang +10

Large language models have repeatedly shown outstanding performance across diverse applications. However, deploying these models can inadvertently risk user privacy. The significan…

cs.AI20241 cited

Tool-Planner: Task Planning with Clusters across Multiple Tools

Yanming Liu, Xinyue Peng, Jiannan Cao +6

Large language models (LLMs) have demonstrated exceptional reasoning capabilities, enabling them to solve various complex problems. Recently, this ability has been applied to the p…

cs.CL2024

ERA-CoT: Improving Chain-of-Thought through Entity Relationship Analysis

Yanming Liu, Xinyue Peng, Tianyu Du +3

Large language models (LLMs) have achieved commendable accomplishments in various natural language processing tasks. However, LLMs still encounter significant challenges when deali…

cs.CL2024

RA-ISF: Learning to Answer and Understand from Retrieval Augmentation via Iterative Self-Feedback

Yanming Liu, Xinyue Peng, Xuhong Zhang +4

Large language models (LLMs) demonstrate exceptional performance in numerous tasks but still heavily rely on knowledge stored in their parameters. Moreover, updating this knowledge…