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Saunshi, Nikunj

  1. Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
    2025/07/07 by Gheorghe Comanici, Eric Bieber, Comanici, Gheorghe +6844 · 8 voices · 1362 citations
    #cs.CL #cs.AI
  2. A Large Self-Annotated Corpus for Sarcasm
    2017/04/19 by Mikhail Khodak, Khodak, Mikhail, Nikunj Saunshi +3 · 1 voice · 7 citations
    #cs.CL #cs.AI #cs.LG
  3. A Theoretical Analysis of Contrastive Unsupervised Representation Learning
    2019/02/25 by Sanjeev Arora, Hrishikesh Khandeparkar, Arora, Sanjeev +7 · 52 citations
    Computer Science · #Domain Adaptation and Few-Shot Learning #Multimodal Machine Learning Applications #Machine Learning and Data Classification
  4. Predicting What You Already Know Helps: Provable Self-Supervised\n Learning
    2020/08/03 by Jason D. Lee, Qi Lei, Lee, Jason D. +5 · 22 citations
    Computer Science · #Domain Adaptation and Few-Shot Learning #Topic Modeling #Machine Learning and Data Classification
  5. Reasoning with Latent Thoughts: On the Power of Looped Transformers
    2025/02/24 by Nikunj Saunshi, Nishanth Dikkala, Saunshi, Nikunj +7 · 34 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Semantic Web and Ontologies
  6. Understanding Contrastive Learning Requires Incorporating Inductive Biases
    2022/02/28 by Nikunj Saunshi, Jordan T. Ash, Saunshi, Nikunj +13 · 6 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and Data Classification
  7. Task-Specific Skill Localization in Fine-tuned Language Models
    2023/02/13 by Abhishek Panigrahi, Panigrahi, Abhishek, Nikunj Saunshi +5 · 7 citations
    Computer Science · #Computation and Language (cs.CL) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Topic Modeling
  8. Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning?
    2024/10/10 by Khashayar Gatmiry, Nikunj Saunshi, Gatmiry, Khashayar +7 · 11 citations
    Computer Science · Engineering · Psychology · #Artificial Intelligence (cs.AI) #Experimental Learning in Engineering #FOS: Computer and information sciences #Intelligent Tutoring Systems and Adaptive Learning #Learning Styles and Cognitive Differences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  9. A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors
    2018/05/14 by Khodak, Mikhail, Saunshi, Nikunj, Liang, Yingyu +3 · 3 citations
    #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences
  10. Learning to Keep a Promise: Scaling Language Model Decoding Parallelism with Learned Asynchronous Decoding
    2025/02/17 by Jin, Tian, Cheng, Ellie Y., Ankner, Zack +6 · 12 citations
    #Computation and Language (cs.CL) #Distributed #FOS: Computer and information sciences #Machine Learning (cs.LG) #Parallel #and Cluster Computing (cs.DC)
  11. Reasoning in Large Language Models Through Symbolic Math Word Problems
    2023/08/03 by Gaur, Vedant, Saunshi, Nikunj · 4 citations
    #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  12. A Sample Complexity Separation between Non-Convex and Convex\n Meta-Learning
    2020/02/25 by Nikunj Saunshi, Yi Zhang, Saunshi, Nikunj +5 · 4 citations
    Computer Science · Engineering · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Machine Learning and ELM #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques
  13. A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks
    2020/10/07 by Nikunj Saunshi, Sadhika Malladi, Saunshi, Nikunj +3 · 3 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Natural Language Processing Techniques #Sentiment Analysis and Opinion Mining #Topic Modeling
  14. Provable Representation Learning for Imitation Learning via Bi-level Optimization
    2020/02/24 by Sanjeev Arora, Arora, Sanjeev, Simon S. Du +7 · 2 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics
  15. On the Inductive Bias of Stacking Towards Improving Reasoning
    2024/09/27 by Nikunj Saunshi, Stefani Karp, Saunshi, Nikunj +9 · 3 citations
    Computer Science · #Advanced Algebra and Logic #Artificial Intelligence (cs.AI) #Computability, Logic, AI Algorithms #Computation and Language (cs.CL) #FOS: Computer and information sciences #Logic, Reasoning, and Knowledge #Machine Learning (cs.LG)
  16. A Little Help Goes a Long Way: Efficient LLM Training by Leveraging Small LMs
    2024/10/24 by Rawat, Ankit Singh, Sadhanala, Veeranjaneyulu, Rostamizadeh, Afshin +12 · 3 citations
    #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  17. A Representation Learning Perspective on the Importance of Train-Validation Splitting in Meta-Learning
    2021/06/29 by Saunshi, Nikunj, Gupta, Arushi, Hu, Wei · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  18. On Predicting Generalization using GANs
    2021/11/28 by Yi Zhang, Zhang, Yi, Arushi Gupta +5 · 1 citation
    Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG)
  19. Understanding Influence Functions and Datamodels via Harmonic Analysis
    2022/10/03 by Saunshi, Nikunj, Gupta, Arushi, Braverman, Mark +1 · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  20. Efficient Stagewise Pretraining via Progressive Subnetworks
    2024/02/08 by Panigrahi, Abhishek, Saunshi, Nikunj, Lyu, Kaifeng +4 · 1 citation
    #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  21. On the Role of Depth and Looping for In-Context Learning with Task Diversity
    2024/10/29 by Khashayar Gatmiry, Gatmiry, Khashayar, Nikunj Saunshi +7 · 1 citation
    Social Sciences · Mathematics · Engineering · #Education Methods and Practices #Cognitive and developmental aspects of mathematical skills #Spatial Cognition and Navigation
  22. StagFormer: Time Staggering Transformer Decoding for RunningLayers In Parallel
    2025/01/26 by Dylan Cutler, Arun Kandoor, Cutler, Dylan +9 · 1 citation
    Computer Science · #Neural Networks and Applications