Sanford, Clayton

1. Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
   2025/07/07 by Gheorghe Comanici, Comanici, Gheorghe, Eric Bieber +6844 · 8 voices · 1398 citations
   #cs.CL #cs.AI
2. Representational Strengths and Limitations of Transformers
   2023/06/05 by Clayton Sanford, Daniel Hsu, Sanford, Clayton +3 · 15 citations
   Computer Science · Engineering · #Stochastic Gradient Optimization Techniques #Advanced Neural Network Applications #Advanced Memory and Neural Computing
3. Learning Single-Index Models with Shallow Neural Networks
   2022/10/27 by Bietti, Alberto, Bruna, Joan, Sanford, Clayton +1 · 12 citations
   #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
4. Understanding Transformer Reasoning Capabilities via Graph Algorithms
   2024/05/28 by Clayton Sanford, Bahare Fatemi, Sanford, Clayton +13 · 18 citations
   Computer Science · #AI-based Problem Solving and Planning #Advanced Software Engineering Methodologies #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Model-Driven Software Engineering Techniques
5. Transformers, parallel computation, and logarithmic depth
   2024/02/14 by Sanford, Clayton, Hsu, Daniel, Telgarsky, Matus · 12 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG)
6. One-layer transformers fail to solve the induction heads task
   2024/08/26 by Sanford, Clayton, Hsu, Daniel, Telgarsky, Matus · 12 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
7. Enabling equation-free modeling via diffusion maps
   2021/12/30 by Chin, Tracy, Ruth, Jacob, Sanford, Clayton +3 · 4 citations
   #Dynamical Systems (math.DS) #FOS: Mathematics
8. Near-Optimal Statistical Query Lower Bounds for Agnostically Learning Intersections of Halfspaces with Gaussian Marginals
   2022/02/10 by Daniel Hsu, Clayton Sanford, Hsu, Daniel +5 · 2 citations
   Computer Science · #FOS: Computer and information sciences #Imbalanced Data Classification Techniques #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and Data Classification
9. Expressivity of Neural Networks via Chaotic Itineraries beyond\n Sharkovsky's Theorem
   2021/10/19 by Clayton Sanford, Vaggos Chatziafratis, Sanford, Clayton +1 · 1 citation
   Computer Science · Engineering · #Advanced Memory and Neural Computing #Chaotic Dynamics (nlin.CD) #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #FOS: Physical sciences #Ferroelectric and Negative Capacitance Devices #Machine Learning (cs.LG) #Neural Networks and Applications
10. Best of Both Worlds: Advantages of Hybrid Graph Sequence Models
    2024/11/23 by Ali Behrouz, Ali Parviz, Behrouz, Ali +9 · 1 voice · 1 citation
    Computer Science · #Advanced Graph Neural Networks #FOS: Computer and information sciences #Graph Theory and Algorithms #Machine Learning (cs.LG) #Social and Information Networks (cs.SI)
11. When Do Transformers Outperform Feedforward and Recurrent Networks? A Statistical Perspective
    2025/03/14 by Alireza Mousavi-Hosseini, Clayton Sanford, Mousavi-Hosseini, Alireza +5 · 1 voice · 1 citation
    #stat.ML #cs.LG
12. Depth-Width tradeoffs in Algorithmic Reasoning of Graph Tasks with Transformers
    2025/03/03 by Yehudai, Gilad, Sanford, Clayton, Bechler-Speicher, Maya +3 · 1 citation
    #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)