24 citations · 66 across the 24 of their papers we have counts for
7 papers · 1 filter
The Road to Artificial SuperIntelligence: A Comprehensive Survey of Superalignment
HyunJin Kim, DongHyun Ryu, Xiaoyuan Yi +6
The emergence of large language models (LLMs) has sparked discussion on Artificial Superintelligence (ASI), a hypothetical AI system that surpasses human intelligence. Although ASI…
Assessing Dialect Fairness and Robustness of Large Language Models in Reasoning Tasks
Fangru Lin, Shaoguang Mao, Emanuele La Malfa +7
Language is not monolithic. While benchmarks, including those designed for multiple languages, are often used as proxies to evaluate the performance of Large Language Models (LLMs)…
Elephant in the Room: Unveiling the Impact of Reward Model Quality in Alignment
Yan Liu, Xiaoyuan Yi, Xiaokang Chen +6
The demand for regulating potentially risky behaviors of large language models (LLMs) has ignited research on alignment methods. Since LLM alignment heavily relies on reward models…
CLAVE: An Adaptive Framework for Evaluating Values of LLM Generated Responses
Jing Yao, Xiaoyuan Yi, Xing Xie
The rapid progress in Large Language Models (LLMs) poses potential risks such as generating unethical content. Assessing LLMs' values can help expose their misalignment, but relies…
RecAI: Leveraging Large Language Models for Next-Generation Recommender Systems
Jianxun Lian, Yuxuan Lei, Xu Huang +3
This paper introduces RecAI, a practical toolkit designed to augment or even revolutionize recommender systems with the advanced capabilities of Large Language Models (LLMs). RecAI…
On the Essence and Prospect: An Investigation of Alignment Approaches for Big Models
Xinpeng Wang, Shitong Duan, Xiaoyuan Yi +7
Big models have achieved revolutionary breakthroughs in the field of AI, but they might also pose potential concerns. Addressing such concerns, alignment technologies were introduc…
Aligning Language Models for Versatile Text-based Item Retrieval
Yuxuan Lei, Jianxun Lian, Jing Yao +3
This paper addresses the gap between general-purpose text embeddings and the specific demands of item retrieval tasks. We demonstrate the shortcomings of existing models in capturi…