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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 …
Alias-Free Mamba Neural Operator - OpenReview
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, …
Weakly-Supervised Affordance Grounding Guided by Part-Level...
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 …
Measuring Mathematical Problem Solving With the MATH Dataset
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.
LLaVA-OneVision: Easy Visual Task Transfer - OpenReview
Feb 9, 2025 · We present LLaVA-OneVision, a family of open large multimodal models (LMMs) developed by consolidating our insights into data, models, and visual representations in the …
Reasoning of Large Language Models over Knowledge Graphs …
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.
Diffusion Generative Modeling for Spatially Resolved Gene...
Jan 22, 2025 · Spatial Transcriptomics (ST) allows a high-resolution measurement of RNA sequence abundance by systematically connecting cell morphology depicted in Hematoxylin …
Thieves on Sesame Street! Model Extraction of BERT-based APIs
Finally, we study two defense strategies against model extraction—membership classification and API watermarking—which while successful against some adversaries can also be …
Probabilistic Learning to Defer: Handling Missing Expert...
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 …
KooNPro: A Variance-Aware Koopman Probabilistic Model
Jan 22, 2025 · The probabilistic forecasting of time series is a well-recognized challenge, particularly in disentangling correlations among interacting time series and addressing the …
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