{"list":"other","total":52,"rows":[{"id":"2009.03300","title":"Measuring Massive Multitask Language Understanding","created":"2020-09-07","cited_by_count":7963},{"id":"1803.05457","title":"Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge","created":"2018-03-14","cited_by_count":4886},{"id":"2108.07732","title":"Program Synthesis with Large Language Models","created":"2021-08-16","cited_by_count":3637},{"id":"1810.03993","title":"Model Cards for Model Reporting","created":"2018-10-05","cited_by_count":1080},{"id":"1804.08328","title":"Taskonomy: Disentangling Task Transfer Learning","created":"2018-04-23","cited_by_count":634},{"id":"2402.14992","title":"tinyBenchmarks: evaluating LLMs with fewer examples","created":"2024-02-22","cited_by_count":310},{"id":"2311.13600","title":"ZipLoRA: Any Subject in Any Style by Effectively Merging LoRAs","created":"2023-11-22","cited_by_count":194},{"id":"2002.12462","title":"LEEP: A New Measure to Evaluate Transferability of Learned Representations","created":"2020-02-27","cited_by_count":188},{"id":"2303.17015","title":"HyperDiffusion: Generating Implicit Neural Fields with Weight-Space Diffusion","created":"2023-03-29","cited_by_count":152},{"id":"2204.10965","title":"CLIP-Dissect: Automatic Description of Neuron Representations in Deep Vision Networks","created":"2022-04-23","cited_by_count":147},{"id":"1908.08142","title":"Transferability and Hardness of Supervised Classification Tasks","created":"2019-08-21","cited_by_count":127},{"id":"2410.19735","title":"Model merging with SVD to tie the Knots","created":"2024-10-25","cited_by_count":122},{"id":"1602.08448","title":"Simple Bayesian Algorithms for Best Arm Identification","created":"2016-02-26","cited_by_count":117},{"id":"2301.12780","title":"Equivariant Architectures for Learning in Deep Weight Spaces","created":"2023-01-30","cited_by_count":107},{"id":"2209.12892","title":"Learning to Learn with Generative Models of Neural Network Checkpoints","created":"2022-09-26","cited_by_count":86},{"id":"2002.05688","title":"Classifying the classifier: dissecting the weight space of neural networks","created":"2020-02-13","cited_by_count":65},{"id":"2402.05859","title":"Learning to Route Among Specialized Experts for Zero-Shot Generalization","created":"2024-02-08","cited_by_count":65},{"id":"2209.14733","title":"Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights","created":"2022-09-29","cited_by_count":64},{"id":"2403.12143","title":"Graph Neural Networks for Learning Equivariant Representations of Neural Networks","created":"2024-03-18","cited_by_count":59},{"id":"2302.04863","title":"Knowledge is a Region in Weight Space for Fine-tuned Language Models","created":"2023-02-09","cited_by_count":58},{"id":"2312.04501","title":"Graph Metanetworks for Processing Diverse Neural Architectures","created":"2023-12-07","cited_by_count":57},{"id":"2212.01378","title":"ColD Fusion: Collaborative Descent for Distributed Multitask Finetuning","created":"2022-12-02","cited_by_count":52},{"id":"2306.09346","title":"Rosetta Neurons: Mining the Common Units in a Model Zoo","created":"2023-06-15","cited_by_count":46},{"id":"2406.09413","title":"Interpreting the Weight Space of Customized Diffusion Models","created":"2024-06-13","cited_by_count":36},{"id":"2506.13018","title":"Symmetry in Neural Network Parameter Spaces","created":"2025-06-16","cited_by_count":36},{"id":"2306.03900","title":"Model Spider: Learning to Rank Pre-Trained Models Efficiently","created":"2023-06-06","cited_by_count":32},{"id":"2401.13822","title":"Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on Hugging Face","created":"2024-01-24","cited_by_count":27},{"id":"2503.10633","title":"We Should Chart an Atlas of All the World's Models","created":"2025-03-13","cited_by_count":25},{"id":"2402.04081","title":"Improved Generalization of Weight Space Networks via Augmentations","created":"2024-02-06","cited_by_count":24},{"id":"2211.00107","title":"Where to start? Analyzing the potential value of intermediate models","created":"2022-10-31","cited_by_count":23},{"id":"2501.18251","title":"How to Select Datapoints for Efficient Human Evaluation of NLG Models?","created":"2025-01-30","cited_by_count":23},{"id":"2410.04207","title":"Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models","created":"2024-10-05","cited_by_count":22},{"id":"2405.20231","title":"The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof","created":"2024-05-30","cited_by_count":21},{"id":"2402.07891","title":"Label-Efficient Model Selection for Text Generation","created":"2024-02-12","cited_by_count":19},{"id":"2404.04671","title":"PhyloLM : Inferring the Phylogeny of Large Language Models and Predicting their Performances in Benchmarks","created":"2024-04-06","cited_by_count":19},{"id":"2404.18928","title":"Stylus: Automatic Adapter Selection for Diffusion Models","created":"2024-04-29","cited_by_count":18},{"id":"2405.13058","title":"The AI Community Building the Future? A Quantitative Analysis of Development Activity on Hugging Face Hub","created":"2024-05-20","cited_by_count":18},{"id":"2410.10811","title":"Deep Linear Probe Generators for Weight Space Learning","created":"2024-10-14","cited_by_count":17},{"id":"2510.00296","title":"Beyond Token Probes: Hallucination Detection via Activation Tensors with ACT-ViT","created":"2025-09-30","cited_by_count":17},{"id":"2402.10208","title":"Recovering the Pre-Fine-Tuning Weights of Generative Models","created":"2024-02-15","cited_by_count":16},{"id":"2403.11998","title":"Learning Useful Representations of Recurrent Neural Network Weight Matrices","created":"2024-03-18","cited_by_count":15},{"id":"2211.08572","title":"Bayesian Fixed-Budget Best-Arm Identification","created":"2022-11-15","cited_by_count":13},{"id":"2503.14043","title":"Beyond Next Token Probabilities: Learnable, Fast Detection of Hallucinations and Data Contamination on LLM Output Distributions","created":"2025-03-18","cited_by_count":12},{"id":"2106.03847","title":"GAN Cocktail: mixing GANs without dataset access","created":"2021-06-07","cited_by_count":8},{"id":"2410.13569","title":"Learning on Model Weights using Tree Experts","created":"2024-10-17","cited_by_count":7},{"id":"2504.20185","title":"AI Supply Chains: An Emerging Ecosystem of AI Actors, Products, and Services","created":"2025-04-28","cited_by_count":7},{"id":"2502.09619","title":"Can this Model Also Recognize Dogs? Zero-Shot Model Search from Weights","created":"2025-02-13","cited_by_count":5},{"id":"2510.02096","title":"Learning Model Representations Using Publicly Available Model Hubs","created":"2025-10-02","cited_by_count":4},{"id":"2512.03073","title":"Economies of Open Intelligence: Tracing Power & Participation in the Model Ecosystem","created":"2025-11-27","cited_by_count":4},{"id":"2506.00741","title":"Data Swarms: Optimizable Generation of Synthetic Evaluation Data","created":"2025-05-31","cited_by_count":2},{"id":"2504.19811","title":"Can a Crow Hatch a Falcon? Lineage Matters in Predicting Large Language Model Performance","created":"2025-04-28","cited_by_count":1},{"id":"2509.23577","title":"ML-Asset Management: Curation, Discovery, and Utilization","created":"2025-09-28","cited_by_count":1}],"next_cursor":null}