9 citations · 26 across the 51 of their papers we have counts for
6 papers · 2 filters
MTA: A Merge-then-Adapt Framework for Personalized Large Language Model
Xiaopeng Li, Yuanjin Zheng, Wanyu Wang +6
Personalized Large Language Models (PLLMs) aim to align model outputs with individual user preferences, a crucial capability for user-centric applications. However, the prevalent a…
Learning a Single Token to Replace Long System Prompts in LLMs
Jiancheng Dong, Pengyue Jia, Jingyu Peng +7
Long system prompts are widely used to steer Large Language Models (LLMs), but repeatedly processing them at inference time is inefficient and consumes valuable context budget. Thi…
AdaSwitch: Balancing Exploration and Guidance in Knowledge Distillation via Adaptive Switching
Jingyu Peng, Maolin Wang, Hengyi Cai +5
Small language models (SLMs) are crucial for applications with strict latency and computational constraints, yet achieving high performance remains challenging. Knowledge distillat…
Put Teacher in Student's Shoes: Cross-Distillation for Ultra-compact Model Compression Framework
Maolin Wang, Jun Chu, Sicong Xie +4
In the era of mobile computing, deploying efficient Natural Language Processing (NLP) models in resource-restricted edge settings presents significant challenges, particularly in e…
Align-GRAG: Anchor and Rationale Guided Dual Alignment for Graph Retrieval-Augmented Generation
Derong Xu, Pengyue Jia, Xiaopeng Li +9
Despite the strong abilities, large language models (LLMs) still suffer from hallucinations and reliance on outdated knowledge, raising concerns in knowledge-intensive tasks. Graph…
Logic Jailbreak: Efficiently Unlocking LLM Safety Restrictions Through Formal Logical Expression
Jingyu Peng, Maolin Wang, Nan Wang +7
Despite substantial advancements in aligning large language models (LLMs) with human values, current safety mechanisms remain susceptible to jailbreak attacks. We hypothesize that…