Evolution Strategies for Deep RL pretraining
Fuente:
arXiv
Saved in:
| Main Authors: | Martínez, Adrian, Gupta, Ananya, Goralija, Hanka, Rico, Mario, Fenollosa, Saúl, Alphaidze, Tamar |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
From BERT to Qwen: Hate Detection across architectures
by: Mon, Ariadna, et al.
Published: (2025)
by: Mon, Ariadna, et al.
Published: (2025)
Explore to Generalize in Zero-Shot RL
by: Zisselman, Ev, et al.
Published: (2023)
by: Zisselman, Ev, et al.
Published: (2023)
Overcoming catastrophic forgetting in neural networks
by: Loke, Brandon Shuen Yi, et al.
Published: (2025)
by: Loke, Brandon Shuen Yi, et al.
Published: (2025)
Predicting VBAC Outcomes from U.S. Natality Data using Deep and Classical Machine Learning Models
by: Anand, Ananya
Published: (2025)
by: Anand, Ananya
Published: (2025)
The effectiveness of MAE pre-pretraining for billion-scale pretraining
by: Singh, Mannat, et al.
Published: (2023)
by: Singh, Mannat, et al.
Published: (2023)
Synthetic continued pretraining
by: Yang, Zitong, et al.
Published: (2024)
by: Yang, Zitong, et al.
Published: (2024)
Multitask finetuning and acceleration of chemical pretrained models for small molecule drug property prediction
by: Adrian, Matthew, et al.
Published: (2025)
by: Adrian, Matthew, et al.
Published: (2025)
Deep Image Priors for Magnetic Resonance Fingerprinting with pretrained Bloch-consistent denoising autoencoders
by: Mayo, Perla, et al.
Published: (2024)
by: Mayo, Perla, et al.
Published: (2024)
Prototype Guided Post-pretraining for Single-Cell Representation Learning
by: Weerasekara, Sachini, et al.
Published: (2026)
by: Weerasekara, Sachini, et al.
Published: (2026)
Curvature-Guided LoRA: Steering in the pretrained NTK subspace
by: Zheng, Frédéric, et al.
Published: (2026)
by: Zheng, Frédéric, et al.
Published: (2026)
SmilesT5: Domain-specific pretraining for molecular language models
by: Spence, Philip, et al.
Published: (2025)
by: Spence, Philip, et al.
Published: (2025)
Next-token pretraining implies in-context learning
by: Riechers, Paul M., et al.
Published: (2025)
by: Riechers, Paul M., et al.
Published: (2025)
Cell Sensing: Traffic detection
by: Fenollosa, Saúl
Published: (2025)
by: Fenollosa, Saúl
Published: (2025)
Universal priors: solving empirical Bayes via Bayesian inference and pretraining
by: Cannella, Nick, et al.
Published: (2026)
by: Cannella, Nick, et al.
Published: (2026)
Bootstrapped Mixed Rewards for RL Post-Training: Injecting Canonical Action Order
by: Gupta, Prakhar, et al.
Published: (2025)
by: Gupta, Prakhar, et al.
Published: (2025)
RL-Guided Data Selection for Language Model Finetuning
by: Jha, Animesh, et al.
Published: (2025)
by: Jha, Animesh, et al.
Published: (2025)
Algorithmic Guarantees for Distilling Supervised and Offline RL Datasets
by: Gupta, Aaryan, et al.
Published: (2025)
by: Gupta, Aaryan, et al.
Published: (2025)
Joint Embedding Predictive Architecture for self-supervised pretraining on polymer molecular graphs
by: Piccoli, Francesco, et al.
Published: (2025)
by: Piccoli, Francesco, et al.
Published: (2025)
Using Quantum Solved Deep Boltzmann Machines to Increase the Data Efficiency of RL Agents
by: Kent, Daniel, et al.
Published: (2024)
by: Kent, Daniel, et al.
Published: (2024)
RL-Obfuscation: Can Language Models Learn to Evade Latent-Space Monitors?
by: Gupta, Rohan, et al.
Published: (2025)
by: Gupta, Rohan, et al.
Published: (2025)
Physics-informed waveform inversion using pretrained wavefield neural operators
by: Huang, Xinquan, et al.
Published: (2025)
by: Huang, Xinquan, et al.
Published: (2025)
Towards a pretrained deep learning estimator of the Linfoot informational correlation
by: Berg, Stéphanie M. van den, et al.
Published: (2025)
by: Berg, Stéphanie M. van den, et al.
Published: (2025)
Value-Based Deep RL Scales Predictably
by: Rybkin, Oleh, et al.
Published: (2025)
by: Rybkin, Oleh, et al.
Published: (2025)
DDLP: Unsupervised Object-Centric Video Prediction with Deep Dynamic Latent Particles
by: Daniel, Tal, et al.
Published: (2023)
by: Daniel, Tal, et al.
Published: (2023)
Boosting deep Reinforcement Learning using pretraining with Logical Options
by: Ye, Zihan, et al.
Published: (2026)
by: Ye, Zihan, et al.
Published: (2026)
TextGram: Towards a better domain-adaptive pretraining
by: Hiwarkhedkar, Sharayu, et al.
Published: (2024)
by: Hiwarkhedkar, Sharayu, et al.
Published: (2024)
SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining
by: Han, Andi, et al.
Published: (2024)
by: Han, Andi, et al.
Published: (2024)
Compute-Optimal Scaling for Value-Based Deep RL
by: Fu, Preston, et al.
Published: (2025)
by: Fu, Preston, et al.
Published: (2025)
Unsupervised Parameter Efficient Source-free Post-pretraining
by: Jha, Abhishek, et al.
Published: (2025)
by: Jha, Abhishek, et al.
Published: (2025)
Do pretrained Transformers Learn In-Context by Gradient Descent?
by: Shen, Lingfeng, et al.
Published: (2023)
by: Shen, Lingfeng, et al.
Published: (2023)
stable-pretraining-v1: Foundation Model Research Made Simple
by: Balestriero, Randall, et al.
Published: (2025)
by: Balestriero, Randall, et al.
Published: (2025)
TiMoE: Time-Aware Mixture of Language Experts
by: Faro, Robin, et al.
Published: (2025)
by: Faro, Robin, et al.
Published: (2025)
Panda: A pretrained forecast model for chaotic dynamics
by: Lai, Jeffrey, et al.
Published: (2025)
by: Lai, Jeffrey, et al.
Published: (2025)
Learning the relative composition of EEG signals using pairwise relative shift pretraining
by: Sandino, Christopher, et al.
Published: (2025)
by: Sandino, Christopher, et al.
Published: (2025)
Context-self contrastive pretraining for crop type semantic segmentation
by: Tarasiou, Michail, et al.
Published: (2021)
by: Tarasiou, Michail, et al.
Published: (2021)
Proving membership in LLM pretraining data via data watermarks
by: Wei, Johnny Tian-Zheng, et al.
Published: (2024)
by: Wei, Johnny Tian-Zheng, et al.
Published: (2024)
Solving Deep Reinforcement Learning Tasks with Evolution Strategies and Linear Policy Networks
by: Wong, Annie, et al.
Published: (2024)
by: Wong, Annie, et al.
Published: (2024)
Test-Time Regret Minimization in Meta Reinforcement Learning
by: Mutti, Mirco, et al.
Published: (2024)
by: Mutti, Mirco, et al.
Published: (2024)
CRISP-NAM: Competing Risks Interpretable Survival Prediction with Neural Additive Models
by: Ramachandram, Dhanesh, et al.
Published: (2025)
by: Ramachandram, Dhanesh, et al.
Published: (2025)
DG-101.INT – Colony Intelligence as a Regulatory Mechanism of Stability
by: Goralija, Dženan
Published: (2026)
by: Goralija, Dženan
Published: (2026)
Similar Items
-
From BERT to Qwen: Hate Detection across architectures
by: Mon, Ariadna, et al.
Published: (2025) -
Explore to Generalize in Zero-Shot RL
by: Zisselman, Ev, et al.
Published: (2023) -
Overcoming catastrophic forgetting in neural networks
by: Loke, Brandon Shuen Yi, et al.
Published: (2025) -
Predicting VBAC Outcomes from U.S. Natality Data using Deep and Classical Machine Learning Models
by: Anand, Ananya
Published: (2025) -
The effectiveness of MAE pre-pretraining for billion-scale pretraining
by: Singh, Mannat, et al.
Published: (2023)