Papers
Can an AI Agent Safely Run a Government? Existence of Probably Approximately Aligned Policies
Frédéric Berdoz, Roger Wattenhofer
Can Graph Learning Improve Planning in LLM-based Agents?
Xixi Wu, Yifei Shen, Caihua Shan et al.
Can Graph Neural Networks Expose Training Data Properties? An Efficient Risk Assessment Approach
Hanyang Yuan, Jiarong Xu, Renhong Huang et al.
Can Language Models Learn to Skip Steps?
Tengxiao Liu, Qipeng Guo, Xiangkun Hu et al.
Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales?
Zhanke Zhou, Rong Tao, Jianing Zhu et al.
Can Large Language Model Agents Simulate Human Trust Behavior?
Feiran Jia, Ziyu Ye, Shiyang Lai et al.
Can Large Language Models Analyze Graphs like Professionals? A Benchmark, Datasets and Models
Xin Li, Weize Chen, Qizhi Chu et al.
Can large language models explore in-context?
Akshay Krishnamurthy, Keegan Harris, Dylan J. Foster et al.
Can Learned Optimization Make Reinforcement Learning Less Difficult?
Alexander D. Goldie, Chris Lu, Matthew T. Jackson et al.
Can LLMs Implicitly Learn Numeric Parameter Constraints in Data Science APIs?
Yinlin Deng, Chunqiu Steven Xia, Zhezhen Cao et al.
Can LLMs Learn by Teaching for Better Reasoning? A Preliminary Study
Xuefei Ning, Zifu Wang, Shiyao Li et al.
Can LLMs Solve Molecule Puzzles? A Multimodal Benchmark for Molecular Structure Elucidation
Kehan Guo, Bozhao Nan, Yujun Zhou et al.
Can Models Learn Skill Composition from Examples?
Haoyu Zhao, Simran Kaur, Dingli Yu et al.
Can neural operators always be continuously discretized?
Takashi Furuya, Michael Puthawala, Maarten V. de Hoop et al.
Can Simple Averaging Defeat Modern Watermarks?
Pei Yang, Hai Ci, Yiren Song et al.
Can Transformers Smell Like Humans?
Farzaneh Taleb, Miguel Vasco, Antônio H. Ribeiro et al.
Can We Leave Deepfake Data Behind in Training Deepfake Detector?
Jikang Cheng, Zhiyuan Yan, Ying Zhang et al.
CaptainCook4D: A Dataset for Understanding Errors in Procedural Activities
Rohith Peddi, Shivvrat Arya, Bharath Challa et al.
Capturing the denoising effect of PCA via compression ratio
Chandra Sekhar Mukherjee, Nikhil Deorkar, Jiapeng Zhang
Cardinality-Aware Set Prediction and Top-$k$ Classification
Corinna Cortes, Anqi Mao, Christopher Mohri et al.
CARE: a Benchmark Suite for the Classification and Retrieval of Enzymes
Jason Yang, Ariane Mora, Shengchao Liu et al.
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models
Peng Xia, Ze Chen, Juanxi Tian et al.
Carrot and Stick: Eliciting Comparison Data and Beyond
Yiling Chen, Shi Feng, Fang-Yi Yu
Cascade of phase transitions in the training of energy-based models
Dimitrios Bachtis, Giulio Biroli, Aurélien Decelle et al.
Cascade Speculative Drafting for Even Faster LLM Inference
Ziyi Chen, Xiaocong Yang, Jiacheng Lin et al.