1 code implementation • 28 May 2024 • Tiansheng Huang, Sihao Hu, Fatih Ilhan, Selim Furkan Tekin, Ling Liu
Recent studies show that Large Language Models (LLMs) with safety alignment can be jail-broken by fine-tuning on a dataset mixed with harmful data.
2 code implementations • 5 Apr 2024 • Selim Furkan Tekin, Fatih Ilhan, Tiansheng Huang, Sihao Hu, Ka-Ho Chow, Margaret L. Loper, Ling Liu
This paper presents FusionShot, a focal diversity optimized few-shot ensemble learning approach for boosting the robustness and generalization performance of pre-trained few-shot models.
1 code implementation • 2 Apr 2024 • Sihao Hu, Tiansheng Huang, Fatih Ilhan, Selim Tekin, Gaowen Liu, Ramana Kompella, Ling Liu
The development of game agents holds a critical role in advancing towards Artificial General Intelligence (AGI).
1 code implementation • 2 Feb 2024 • Tiansheng Huang, Sihao Hu, Ling Liu
The new paradigm of finetuning-as-a-service introduces a new attack surface for Large Language Models (LLMs): a few harmful data uploaded by users can easily trick the finetuning to produce an alignment-broken model.
1 code implementation • 2 Feb 2024 • Sihao Hu, Tiansheng Huang, Ling Liu
We introduce PokeLLMon, the first LLM-embodied agent that achieves human-parity performance in tactical battle games, as demonstrated in Pokemon battles.
1 code implementation • 2 Oct 2023 • Sihao Hu, Tiansheng Huang, Fatih İlhan, Selim Furkan Tekin, Ling Liu
The goal of auditor is to yield a broad spectrum of vulnerabilities with the hope of encompassing the correct answer, whereas the goal of critic that evaluates the validity of identified vulnerabilities is to minimize the number of false positives.
1 code implementation • 29 Mar 2023 • Sihao Hu, Zhen Zhang, Bingqiao Luo, Shengliang Lu, Bingsheng He, Ling Liu
As various forms of fraud proliferate on Ethereum, it is imperative to safeguard against these malicious activities to protect susceptible users from being victimized.
1 code implementation • 15 Jan 2023 • Fatih Ilhan, Ka-Ho Chow, Sihao Hu, Tiansheng Huang, Selim Tekin, Wenqi Wei, Yanzhao Wu, Myungjin Lee, Ramana Kompella, Hugo Latapie, Gaowen Liu, Ling Liu
Instead of having every sample go through all DNN layers during prediction, EENet learns an early exit scheduler, which can intelligently terminate the inference earlier for certain predictions, which the model has high confidence of early exit.
no code implementations • 16 Nov 2022 • Yaxian Xia, Yi Cao, Sihao Hu, Tong Liu, Lingling Lu
We identify that the key to TIRA is to extract customers' personalized entering intention and weigh the impact of triggers based on this intention.
1 code implementation • 21 Apr 2022 • Sihao Hu, Zhen Zhang, Shengliang Lu, Bingsheng He, Zhao Li
With the proliferation of pump-and-dump schemes (P&Ds) in the cryptocurrency market, it becomes imperative to detect such fraudulent activities in advance to alert potentially susceptible investors.
1 code implementation • 21 Feb 2022 • Sihao Hu, Yi Cao, Yu Gong, Zhao Li, Yazheng Yang, Qingwen Liu, Shouling Ji
Specifically, we establish a heterogeneous graph that contains physical and semantic linkages to guide the feature transfer process from warmed-up video to cold-start videos.
no code implementations • 17 Sep 2021 • Xinyuan Qi, Kai Hou, Tong Liu, Zhongzhong Yu, Sihao Hu, Wenwu Ou
Except for introducing future knowledge for prediction, we propose Aliformer based on the bidirectional Transformer, which can utilize the historical information, current factor, and future knowledge to predict future sales.