activity
20242026
collaborators

7 papers

cs.AI2026

ELAIPBench: A Benchmark for Expert-Level Artificial Intelligence Paper Understanding

Xinbang Dai, Huikang Hu, Yongrui Chen +6

While large language models (LLMs) excel at many domain-specific tasks, their ability to deeply comprehend and reason about full-length academic papers remains underexplored. Exist…

cs.CL2026

After Retrieval, Before Generation: Enhancing the Trustworthiness of Large Language Models in Retrieval-Augmented Generation

Xinbang Dai, Huikang Hu, Yuncheng Hua +5

Retrieval-augmented generation (RAG) is a promising paradigm, yet its trustworthiness remains a critical concern. A major vulnerability arises prior to generation: models often fai…

cs.CL2025

Pandora: A Code-Driven Large Language Model Agent for Unified Reasoning Across Diverse Structured Knowledge

Yongrui Chen, Junhao He, Linbo Fu +10

Unified Structured Knowledge Reasoning (USKR) aims to answer natural language questions (NLQs) by using structured sources such as tables, databases, and knowledge graphs in a unif…

cs.CL2025

Pandora: Leveraging Code-driven Knowledge Transfer for Unified Structured Knowledge Reasoning

Yongrui Chen, Junhao He, Linbo Fu +10

Unified Structured Knowledge Reasoning (USKR) aims to answer natural language questions by using structured sources such as tables, databases, and knowledge graphs in a unified way…

cs.CR2025

Dual-Priv Pruning : Efficient Differential Private Fine-Tuning in Multimodal Large Language Models

Qianshan Wei, Jiaqi Li, Zihan You +9

Differential Privacy (DP) is a widely adopted technique, valued for its effectiveness in protecting the privacy of task-specific datasets, making it a critical tool for large langu…

cs.CV2025

Single Image Unlearning: Efficient Machine Unlearning in Multimodal Large Language Models

Jiaqi Li, Qianshan Wei, Chuanyi Zhang +5

Machine unlearning empowers individuals with the `right to be forgotten' by removing their private or sensitive information encoded in machine learning models. However, it remains…