Summary of Can Graph Neural Networks Learn Language with Extremely Weak Text Supervision?, by Zihao Li et al.
Can Graph Neural Networks Learn Language with Extremely Weak Text Supervision?by Zihao Li, Lecheng Zheng,…
Summary of Hyperband-based Bayesian Optimization For Black-box Prompt Selection, by Lennart Schneider and Martin Wistuba and Aaron Klein and Jacek Golebiowski and Giovanni Zappella and Felice Antonio Merra
Hyperband-based Bayesian Optimization for Black-box Prompt Selectionby Lennart Schneider, Martin Wistuba, Aaron Klein, Jacek Golebiowski,…
Summary of Proactive Agents For Multi-turn Text-to-image Generation Under Uncertainty, by Meera Hahn et al.
Proactive Agents for Multi-Turn Text-to-Image Generation Under Uncertaintyby Meera Hahn, Wenjun Zeng, Nithish Kannen, Rich…
Summary of Enhancing Llms For Physics Problem-solving Using Reinforcement Learning with Human-ai Feedback, by Avinash Anand et al.
Enhancing LLMs for Physics Problem-Solving using Reinforcement Learning with Human-AI Feedbackby Avinash Anand, Kritarth Prasad,…
Summary of Exploring Critical Testing Scenarios For Decision-making Policies: An Llm Approach, by Weichao Xu et al.
Exploring Critical Testing Scenarios for Decision-Making Policies: An LLM Approachby Weichao Xu, Huaxin Pei, Jingxuan…
Summary of Integrating Expert Labels Into Llm-based Emission Goal Detection: Example Selection Vs Automatic Prompt Design, by Marco Wrzalik et al.
Integrating Expert Labels into LLM-based Emission Goal Detection: Example Selection vs Automatic Prompt Designby Marco…
Summary of Does Rlhf Scale? Exploring the Impacts From Data, Model, and Method, by Zhenyu Hou et al.
Does RLHF Scale? Exploring the Impacts From Data, Model, and Methodby Zhenyu Hou, Pengfan Du,…
Summary of Language Hooks: a Modular Framework For Augmenting Llm Reasoning That Decouples Tool Usage From the Model and Its Prompt, by Damien De Mijolla et al.
Language hooks: a modular framework for augmenting LLM reasoning that decouples tool usage from the…
Summary of Memory-enhanced Invariant Prompt Learning For Urban Flow Prediction Under Distribution Shifts, by Haiyang Jiang and Tong Chen and Wentao Zhang and Nguyen Quoc Viet Hung and Yuan Yuan and Yong Li and Lizhen Cui
Memory-enhanced Invariant Prompt Learning for Urban Flow Prediction under Distribution Shiftsby Haiyang Jiang, Tong Chen,…
Summary of Sparse Autoencoders Reveal Selective Remapping Of Visual Concepts During Adaptation, by Hyesu Lim et al.
Sparse autoencoders reveal selective remapping of visual concepts during adaptationby Hyesu Lim, Jinho Choi, Jaegul…