Cover Image

Predictive Coding for Decision Transformer

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Luu, Tung M., Lee, Donghoon, Yoo, Chang D.
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Sample Efficient Reinforcement Learning via Large Vision Language Model Distillation
by: Lee, Donghoon, et al.
Published: (2025)

Policy Learning from Large Vision-Language Model Feedback without Reward Modeling
by: Luu, Tung M., et al.
Published: (2025)

Reward Generation via Large Vision-Language Model in Offline Reinforcement Learning
by: Lee, Younghwan, et al.
Published: (2025)

Enhancing Rating-Based Reinforcement Learning to Effectively Leverage Feedback from Large Vision-Language Models
by: Luu, Tung Minh, et al.
Published: (2025)

On the Perturbed States for Transformed Input-robust Reinforcement Learning
by: Luu, Tung M., et al.
Published: (2024)

Towards Robust Policy: Enhancing Offline Reinforcement Learning with Adversarial Attacks and Defenses
by: Nguyen, Thanh, et al.
Published: (2024)

Uncertainty-Aware Rank-One MIMO Q Network Framework for Accelerated Offline Reinforcement Learning
by: Nguyen, Thanh, et al.
Published: (2026)

Mitigating Adversarial Perturbations for Deep Reinforcement Learning via Vector Quantization
by: Luu, Tung M., et al.
Published: (2024)

Offline Policy Learning via Skill-step Abstraction for Long-horizon Goal-Conditioned Tasks
by: Kim, Donghoon, et al.
Published: (2024)

Prediction Loss Guided Decision-Focused Learning
by: Jeon, Haeun, et al.
Published: (2025)

Enhancing Knowledge Tracing with Concept Map and Response Disentanglement
by: Park, Soonwook, et al.
Published: (2024)

DriVLM: Domain Adaptation of Vision-Language Models in Autonomous Driving
by: Zheng, Xuran, et al.
Published: (2025)

One-Step Flow Q-Learning: Addressing the Diffusion Policy Bottleneck in Offline Reinforcement Learning
by: Nguyen, Thanh, et al.
Published: (2025)

Decision-Focused Learning via Tangent-Space Projection of Prediction Error
by: Lee, Junhyeong, et al.
Published: (2026)

Predictive Prompt Analysis
by: Lee, Jae Yong, et al.
Published: (2025)

Software Vulnerability Prediction in Low-Resource Languages: An Empirical Study of CodeBERT and ChatGPT
by: Le, Triet H. M., et al.
Published: (2024)

Abundance-Aware Set Transformer for Microbiome Sample Embedding
by: Yoo, Hyunwoo, et al.
Published: (2025)

Towards the Training of Deeper Predictive Coding Neural Networks
by: Qi, Chang, et al.
Published: (2025)

Spiking Decision Transformers: Local Plasticity, Phase-Coding, and Dendritic Routing for Low-Power Sequence Control
by: Pandey, Vishal, et al.
Published: (2025)

Gradient Boosting Decision Tree with LSTM for Investment Prediction
by: Yu, Chang, et al.
Published: (2025)

Pretraining Decision Transformers with Reward Prediction for In-Context Multi-task Structured Bandit Learning
by: Mukherjee, Subhojyoti, et al.
Published: (2024)

Transformer Conformal Prediction for Time Series
by: Lee, Junghwan, et al.
Published: (2024)

Don't Transform the Code, Code the Transforms: Towards Precise Code Rewriting using LLMs
by: Cummins, Chris, et al.
Published: (2024)

Return-Aligned Decision Transformer
by: Tanaka, Tsunehiko, et al.
Published: (2024)

Multi-Agent Inverted Transformer for Flight Trajectory Prediction
by: Yoon, Seokbin, et al.
Published: (2025)

MART: MultiscAle Relational Transformer Networks for Multi-agent Trajectory Prediction
by: Lee, Seongju, et al.
Published: (2024)

Quantifying and Improving Adaptivity in Conformal Prediction through Input Transformations
by: Jang, Sooyong, et al.
Published: (2025)

Predictive Coding beyond Correlations
by: Salvatori, Tommaso, et al.
Published: (2023)

Probing the Decision Boundaries of In-context Learning in Large Language Models
by: Zhao, Siyan, et al.
Published: (2024)

Topology-Guided Knowledge Distillation for Efficient Point Cloud Processing
by: Hai, Luu Tung, et al.
Published: (2025)

Code-Switching Curriculum Learning for Multilingual Transfer in LLMs
by: Yoo, Haneul, et al.
Published: (2024)

Beyond the Frontier: Stochastic Backtracking for Efficient Test-Time Scaling
by: Tran, Dao, et al.
Published: (2026)

Unifying Prediction and Explanation in Time-Series Transformers via Shapley-based Pretraining
by: Cheng, Qisen, et al.
Published: (2025)

Leveraging Predictive Equivalence in Decision Trees
by: McTavish, Hayden, et al.
Published: (2025)

Radar: Fast Long-Context Decoding for Any Transformer
by: Hao, Yongchang, et al.
Published: (2025)

Adversarially Robust Decision Transformer
by: Tang, Xiaohang, et al.
Published: (2024)

Beyond the Known: Decision Making with Counterfactual Reasoning Decision Transformer
by: Nguyen, Minh Hoang, et al.
Published: (2025)

Covariance-Aware Transformers for Quadratic Programming and Decision Making
by: Tire, Kutay, et al.
Published: (2026)

Prompt Tuning Decision Transformers with Structured and Scalable Bandits
by: Rietz, Finn, et al.
Published: (2025)

Querying Easily Flip-flopped Samples for Deep Active Learning
by: Cho, Seong Jin, et al.
Published: (2024)