Summary of Large Language Models Can Be Zero-shot Anomaly Detectors For Time Series?, by Sarah Alnegheimish et al.
Large language models can be zero-shot anomaly detectors for time series?by Sarah Alnegheimish, Linh Nguyen,…
Large language models can be zero-shot anomaly detectors for time series?by Sarah Alnegheimish, Linh Nguyen,…
Mixture of Experts Meets Prompt-Based Continual Learningby Minh Le, An Nguyen, Huy Nguyen, Trang Nguyen,…
Large Language Models are Effective Priors for Causal Graph Discoveryby Victor-Alexandru Darvariu, Stephen Hailes, Mirco…
LLM Processes: Numerical Predictive Distributions Conditioned on Natural Languageby James Requeima, John Bronskill, Dami Choi,…
Prompt-Based Spatio-Temporal Graph Transfer Learningby Junfeng Hu, Xu Liu, Zhencheng Fan, Yifang Yin, Shili Xiang,…
Dynamic Embeddings with Task-Oriented promptingby Allmin Balloccu, Jack ZhangFirst submitted to arxiv on: 17 May…
Latent State Estimation Helps UI Agents to Reasonby William E Bishop, Alice Li, Christopher Rawles,…
Cross-Language Assessment of Mathematical Capability of ChatGPTby Gargi Sathe, Aneesh Shamraj, Aditya Surve, Nahush Patil,…
Simultaneous Masking, Not Prompting Optimization: A Paradigm Shift in Fine-tuning LLMs for Simultaneous Translationby Matthew…
Not All Prompts Are Secure: A Switchable Backdoor Attack Against Pre-trained Vision Transformersby Sheng Yang,…