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20242026
most citedThe Road to Artificial SuperIntelligence: A Comprehensive Survey of Superalignment

1 citations · 1 across the 2 of their papers we have counts for

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15 papers

cs.LG20261 cited

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…

cs.CV2026

Proact-VL: A Proactive VideoLLM for Real-Time AI Companions

Weicai Yan, Yuhong Dai, Qi Ran +6

Proactive and real-time interactive experiences are essential for human-like AI companions, yet face three key challenges: (1) achieving low-latency inference under continuous stre…

cs.AI2026

Does Theory of Mind Improvement Really Benefit Human-AI Interactions? Empirical Findings from Interactive Evaluations

Nanxu Gong, Zixin Chen, Haotian Li +5

Improving the Theory of Mind (ToM) capability of Large Language Models (LLMs) is crucial for effective social interactions between these AI models and humans. However, the existing…

cs.AI2026

To Think or Not To Think, That is The Question for Large Reasoning Models in Theory of Mind Tasks

Nanxu Gong, Haotian Li, Sixun Dong +3

Theory of Mind (ToM) assesses whether models can infer hidden mental states such as beliefs, desires, and intentions, which is essential for natural social interaction. Although re…

cs.CL2026

HumanLLM: Towards Personalized Understanding and Simulation of Human Nature

Yuxuan Lei, Tianfu Wang, Jianxun Lian +3

Motivated by the remarkable progress of large language models (LLMs) in objective tasks like mathematics and coding, there is growing interest in their potential to simulate human…

cs.IR2026

Eliminating Out-of-Domain Recommendations in LLM-based Recommender Systems: A Unified View

Hao Liao, Jiwei Zhang, Jianxun Lian +7

Recommender systems based on Large Language Models (LLMs) are often plagued by hallucinations of out-of-domain (OOD) items. To address this, we propose RecLM, a unified framework t…