Papers
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization
Agustinus Kristiadi, Felix Dangel, Philipp Hennig
The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs
Laura Ruis, Akbir Khan, Stella Biderman et al.
The Grand Illusion: The Myth of Software Portability and Implications for ML Progress.
Fraser Mince, Dzung Dinh, Jonas Kgomo et al.
The Graph Pencil Method: Mapping Subgraph Densities to Stochastic Block Models
Lee Gunderson, Gecia Bravo-Hermsdorff, Peter Orbanz
The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications
Mirac Suzgun, Luke Melas-Kyriazi, Suproteem Sarkar et al.
The Impact of Positional Encoding on Length Generalization in Transformers
Amirhossein Kazemnejad, Inkit Padhi, Karthikeyan Natesan Ramamurthy et al.
The Learnability of In-Context Learning
Noam Wies, Yoav Levine, Amnon Shashua
The Memory-Perturbation Equation: Understanding Model's Sensitivity to Data
Peter Nickl, Lu Xu, Dharmesh Tailor et al.
The noise level in linear regression with dependent data
Ingvar Ziemann, Stephen Tu, George J. Pappas et al.
Theoretical Analysis of the Inductive Biases in Deep Convolutional Networks
Zihao Wang, Lei Wu
Theoretical and Practical Perspectives on what Influence Functions Do
Andrea Schioppa, Katja Filippova, Ivan Titov et al.
Theoretically Guaranteed Bidirectional Data Rectification for Robust Sequential Recommendation
Yatong Sun, Bin Wang, Zhu Sun et al.
The Pick-to-Learn Algorithm: Empowering Compression for Tight Generalization Bounds and Improved Post-training Performance
Dario Paccagnan, Marco Campi, Simone Garatti
The probability flow ODE is provably fast
Sitan Chen, Sinho Chewi, Holden Lee et al.
The Pursuit of Human Labeling: A New Perspective on Unsupervised Learning
Artyom Gadetsky, Maria Brbic
The Quantization Model of Neural Scaling
Eric Michaud, Ziming Liu, Uzay Girit et al.
The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions
Jonathan Schmidt, Philipp Hennig, Jörg Nick et al.
The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance
Jon Donnelly, Srikar Katta, Cynthia Rudin et al.
The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data Only
Guilherme Penedo, Quentin Malartic, Daniel Hesslow et al.
The Rise of AI Language Pathologists: Exploring Two-level Prompt Learning for Few-shot Weakly-supervised Whole Slide Image Classification
Linhao Qu, xiaoyuan luo, Kexue Fu et al.
The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit
Lorenzo Noci, Chuning Li, Mufan Li et al.
The Surprising Effectiveness of Diffusion Models for Optical Flow and Monocular Depth Estimation
Saurabh Saxena, Charles Herrmann, Junhwa Hur et al.
The s-value: evaluating stability with respect to distributional shifts
Suyash Gupta, Dominik Rothenhäusler
The Target-Charging Technique for Privacy Analysis across Interactive Computations
Edith Cohen, Xin Lyu