9 citations · 19 across the 8 of their papers we have counts for
10 papers
CLAQS: Compact Learnable All-Quantum Token Mixer with Shared-ansatz for Text Classification
Junhao Chen, Yifan Zhou, Hanqi Jiang +6
Quantum compute is scaling fast, from cloud QPUs to high throughput GPU simulators, making it timely to prototype quantum NLP beyond toy tasks. However, devices remain qubit limite…
Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges
Haoran Lu, Luyang Fang, Ruidong Zhang +47
Due to the remarkable capabilities and growing impact of large language models (LLMs), they have been deeply integrated into many aspects of society. Thus, ensuring their alignment…
Efficient Multi-Task Inferencing: Model Merging with Gromov-Wasserstein Feature Alignment
Luyang Fang, Ehsan Latif, Haoran Lu +3
Automatic scoring of student responses enhances efficiency in education, but deploying a separate neural network for each task increases storage demands, maintenance efforts, and r…
From Task-Specific Models to Unified Systems: A Review of Model Merging Approaches
Wei Ruan, Tianze Yang, Yifan Zhou +2
Model merging has achieved significant success, with numerous innovative methods proposed to enhance capabilities by combining multiple models. However, challenges persist due to t…
Can OpenAI o1 outperform humans in higher-order cognitive thinking?
Ehsan Latif, Yifan Zhou, Shuchen Guo +6
This study evaluates the performance of OpenAI's o1-preview model in higher-order cognitive domains, including critical thinking, systematic thinking, computational thinking, data…
QueEn: A Large Language Model for Quechua-English Translation
Junhao Chen, Peng Shu, Yiwei Li +7
Recent studies show that large language models (LLMs) are powerful tools for working with natural language, bringing advances in many areas of computational linguistics. However, t…