016 namely CLEVER, which is augmentation-free 017 and mitigates biases on the inference stage. 018 Specifically, we train a claim-evidence fusion 019 model and a claim-only model …

Oct 18, 2021 · To find the limits of Transformers, we collected 12,500 math problems. While a three-time IMO gold medalist got 90%, GPT-3 models got ~5%, with accuracy increasing slowly.

Sep 25, 2024 · Functionally, MambaNO achieves a clever balance between global integration, facilitated by state space model of Mamba that scans the entire function, and local integration, …

Dec 19, 2019 · Finally, we study two defense strategies against model extraction—membership classification and API watermarking—which while successful against some adversaries can …

Jan 22, 2025 · In this work, we focus on the task of weakly supervised affordance grounding, where a model is trained to identify affordance regions on objects using human-object …

Feb 1, 2023 · Abstract: We propose a conditional positional encoding (CPE) scheme for vision Transformers. Unlike previous fixed or learnable positional encodings that are predefined and …

Jan 22, 2025 · While large language models (LLMs) have made significant progress in processing and reasoning over knowledge graphs, current methods suffer from a high non-retrieval rate.

Jan 22, 2025 · Cascades and speculative decoding are two common approaches to improving language models' inference efficiency. Both approaches interleave two models, but via …

Jan 22, 2025 · Recent progress in machine learning research is gradually shifting its focus towards *human-AI cooperation* due to the advantages of exploiting the reliability of human …

Dec 19, 2019 · Abstract: Overparameterization has been shown to benefit both the optimization and generalization of neural networks, but large networks are resource hungry at both training …