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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 …
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.
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, …
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.
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 …
Union-over-Intersections: Object Detection beyond Winner-Takes-All
Jan 22, 2025 · This paper revisits the problem of predicting box locations in object detection architectures. Typically, each box proposal or box query aims to directly maximize the …
Progressive Compression with Universally Quantized Diffusion …
Jan 22, 2025 · Diffusion probabilistic models have achieved mainstream success in many generative modeling tasks, from image generation to inverse problem solving.
Accelerating 3D Molecule Generation via Jointly Geometric …
Jan 22, 2025 · This paper proposes a new 3D molecule generation framework, called GOAT, for fast and effective 3D molecule generation based on the flow-matching optimal transport objective.
Local-Prompt: Extensible Local Prompts for Few-Shot...
Jan 22, 2025 · Keywords: Out-of-distribution detection, Prompt learning, Vision-language model, Few-shot learning
NetMoE: Accelerating MoE Training through Dynamic Sample …
Jan 22, 2025 · Mixture of Experts (MoE) is a widely used technique to expand model sizes for better model quality while maintaining the computation cost constant.
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