Adaptive Retrieval helps Reasoning in LLMs -- but mostly if it's not used
Fuente:
arXiv
Saved in:
| Main Authors: | Shakya, Srijan, Hartl, Anamaria-Roberta, Hochreiter, Sepp, Pöppel, Korbinian |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Point Process Model for Optimizing Repeated Personalized Action Delivery to Users
by: Merkov, Alexander, et al.
Published: (2025)
by: Merkov, Alexander, et al.
Published: (2025)
Leveraging Non-Decimated Wavelet Packet Features and Transformer Models for Time Series Forecasting
by: Nason, Guy P, et al.
Published: (2024)
by: Nason, Guy P, et al.
Published: (2024)
Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian Inference
by: Wang, Zheyu Oliver, et al.
Published: (2023)
by: Wang, Zheyu Oliver, et al.
Published: (2023)
Measuring Neural Network Complexity via Effective Degrees of Freedom
by: Zhou, Jia, et al.
Published: (2026)
by: Zhou, Jia, et al.
Published: (2026)
Custom Loss Functions in Fuel Moisture Modeling
by: Hirschi, Jonathon
Published: (2025)
by: Hirschi, Jonathon
Published: (2025)
Revisiting semi-supervised training objectives for differentiable particle filters
by: Li, Jiaxi, et al.
Published: (2024)
by: Li, Jiaxi, et al.
Published: (2024)
FlashRNN: I/O-Aware Optimization of Traditional RNNs on modern hardware
by: Pöppel, Korbinian, et al.
Published: (2024)
by: Pöppel, Korbinian, et al.
Published: (2024)
Drift Estimation for Diffusion Processes Using Neural Networks Based on Discretely Observed Independent Paths
by: Zhao, Yuzhen, et al.
Published: (2025)
by: Zhao, Yuzhen, et al.
Published: (2025)
Using Artificial Neural Networks to Predict Claim Duration in a Work Injury Compensation Environment
by: Almudevar, Anthony
Published: (2026)
by: Almudevar, Anthony
Published: (2026)
Generalization error bounds for two-layer neural networks with Lipschitz loss function
by: Nguwi, Jiang Yu, et al.
Published: (2026)
by: Nguwi, Jiang Yu, et al.
Published: (2026)
Random Vector Functional Link Networks for Function Approximation on Manifolds
by: Needell, Deanna, et al.
Published: (2020)
by: Needell, Deanna, et al.
Published: (2020)
The Predictive-Causal Gap: An Impossibility Theorem and Large-Scale Neural Evidence
by: Liu, Kejun
Published: (2026)
by: Liu, Kejun
Published: (2026)
Universal Adaptive Environment Discovery
by: Matymov, Madi, et al.
Published: (2025)
by: Matymov, Madi, et al.
Published: (2025)
Critical Points of Random Neural Networks
by: Di Lillo, Simmaco
Published: (2025)
by: Di Lillo, Simmaco
Published: (2025)
Tiled Flash Linear Attention: More Efficient Linear RNN and xLSTM Kernels
by: Beck, Maximilian, et al.
Published: (2025)
by: Beck, Maximilian, et al.
Published: (2025)
A Complete Symmetry Classification of Shallow ReLU Networks
by: Ramakrishnan, Pranavkrishnan
Published: (2026)
by: Ramakrishnan, Pranavkrishnan
Published: (2026)
Learning non-equilibrium diffusions with Schrödinger bridges: from exactly solvable to simulation-free
by: Zhang, Stephen Y., et al.
Published: (2025)
by: Zhang, Stephen Y., et al.
Published: (2025)
Sharp Bounds on the Approximation Rates, Metric Entropy, and $n$-widths of Shallow Neural Networks
by: Siegel, Jonathan W., et al.
Published: (2021)
by: Siegel, Jonathan W., et al.
Published: (2021)
Fractal and Regular Geometry of Deep Neural Networks
by: Di Lillo, Simmaco, et al.
Published: (2025)
by: Di Lillo, Simmaco, et al.
Published: (2025)
Log-Gaussian Gamma Processes for Training Bayesian Neural Networks in Raman and CARS Spectroscopies
by: Härkönen, Teemu, et al.
Published: (2023)
by: Härkönen, Teemu, et al.
Published: (2023)
A Distribution-to-Distribution Neural Probabilistic Forecasting Framework for Dynamical Systems
by: Yang, Tianlin, et al.
Published: (2026)
by: Yang, Tianlin, et al.
Published: (2026)
Designing Time-Series Models With Hypernetworks & Adversarial Portfolios
by: Staněk, Filip
Published: (2024)
by: Staněk, Filip
Published: (2024)
ASNN: Learning to Suggest Neural Architectures from Performance Distributions
by: Hong, Jinwook
Published: (2025)
by: Hong, Jinwook
Published: (2025)
Towards an Algebraic Framework For Approximating Functions Using Neural Network Polynomials
by: Rafi, Shakil, et al.
Published: (2024)
by: Rafi, Shakil, et al.
Published: (2024)
From Theory to Application: A Practical Introduction to Neural Operators in Scientific Computing
by: Jha, Prashant K.
Published: (2025)
by: Jha, Prashant K.
Published: (2025)
pLSTM: parallelizable Linear Source Transition Mark networks
by: Pöppel, Korbinian, et al.
Published: (2025)
by: Pöppel, Korbinian, et al.
Published: (2025)
Optimizing Data Augmentation through Bayesian Model Selection
by: Matymov, Madi, et al.
Published: (2025)
by: Matymov, Madi, et al.
Published: (2025)
Efficient reconstruction of multidimensional random field models with heterogeneous data using stochastic neural networks
by: Xia, Mingtao, et al.
Published: (2025)
by: Xia, Mingtao, et al.
Published: (2025)
Efficient Time-Series Approximation with Linear Recurrent Neural Networks: Architecture Learning and Predictive Power
by: Stolzenburg, Frieder, et al.
Published: (2018)
by: Stolzenburg, Frieder, et al.
Published: (2018)
Deep Neural Networks for Doubly Robust Estimation with Nonprobability Survey Samples
by: Dai, Yufang, et al.
Published: (2026)
by: Dai, Yufang, et al.
Published: (2026)
Minimaxity and Admissibility of Bayesian Neural Networks
by: Coulson, Daniel Andrew, et al.
Published: (2026)
by: Coulson, Daniel Andrew, et al.
Published: (2026)
In almost all shallow analytic neural network optimization landscapes, efficient minimizers have strongly convex neighborhoods
by: Benning, Felix, et al.
Published: (2025)
by: Benning, Felix, et al.
Published: (2025)
Adaptive deep density approximation for stochastic dynamical systems
by: He, Junjie, et al.
Published: (2024)
by: He, Junjie, et al.
Published: (2024)
Approximation Rates for Shallow ReLU$^k$ Neural Networks on Sobolev Spaces via the Radon Transform
by: Mao, Tong, et al.
Published: (2024)
by: Mao, Tong, et al.
Published: (2024)
Optimal Approximation Rates for Deep ReLU Neural Networks on Sobolev and Besov Spaces
by: Siegel, Jonathan W.
Published: (2022)
by: Siegel, Jonathan W.
Published: (2022)
Vision-LSTM: xLSTM as Generic Vision Backbone
by: Alkin, Benedikt, et al.
Published: (2024)
by: Alkin, Benedikt, et al.
Published: (2024)
Generalization and Feature Attribution in Machine Learning Models for Crop Yield and Anomaly Prediction in Germany
by: Baatz, Roland
Published: (2025)
by: Baatz, Roland
Published: (2025)
Global $\mathcal{L}^2$ minimization at uniform exponential rate via geometrically adapted gradient descent in Deep Learning
by: Chen, Thomas
Published: (2023)
by: Chen, Thomas
Published: (2023)
Architecture independent generalization bounds for overparametrized deep ReLU networks
by: Bapu, Anandatheertha, et al.
Published: (2025)
by: Bapu, Anandatheertha, et al.
Published: (2025)
Zero loss guarantees and explicit minimizers for generic overparametrized Deep Learning networks
by: Chen, Thomas, et al.
Published: (2025)
by: Chen, Thomas, et al.
Published: (2025)
Similar Items
-
A Point Process Model for Optimizing Repeated Personalized Action Delivery to Users
by: Merkov, Alexander, et al.
Published: (2025) -
Leveraging Non-Decimated Wavelet Packet Features and Transformer Models for Time Series Forecasting
by: Nason, Guy P, et al.
Published: (2024) -
Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian Inference
by: Wang, Zheyu Oliver, et al.
Published: (2023) -
Measuring Neural Network Complexity via Effective Degrees of Freedom
by: Zhou, Jia, et al.
Published: (2026) -
Custom Loss Functions in Fuel Moisture Modeling
by: Hirschi, Jonathon
Published: (2025)