Seq2Seq2Seq: Lossless Data Compression via Discrete Latent Transformers and Reinforcement Learning

arXiv:2602.12146 · cs.AI, cs.CL, cs.IT, math.IT · Submitted 2026-02-12 · Read on arXiv

cs.AI, cs.CL, cs.IT, math.IT

Submitted: 2026-02-12

Updated: 2026-02-12

Terminology

• Transformer — 25× in this paper · explained in 2 episodes
• Reinforcement Learning — 18× in this paper · explained in 4 episodes
• Actor — 9× in this paper · explained in 3 episodes
• Redundancy — 7× in this paper · explained in 2 episodes
• Attention Mechanism — 6× in this paper · explained in 3 episodes
• Reward Function — 6× in this paper · explained in 2 episodes
• Vector Representations — 6× in this paper · explained in 2 episodes
• Embeddings — 5× in this paper · explained in 2 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Adam — 3× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Transformer Architecture — 3× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Intermediate Representation — 2× in this paper
• Latent Space — 2× in this paper · explained in 7 episodes
• Quantization — 2× in this paper · explained in 12 episodes
• Reinforcement Learning (RL) — 2× in this paper · explained in 25 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Ablation Studies — 1× in this paper · explained in 1 episode
• Activation Function — 1× in this paper · explained in 1 episode
• Adaptability — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Ensemble Learning — 1× in this paper · explained in 2 episodes
• Feature Engineering — 1× in this paper · explained in 3 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Knowledge Graph — 1× in this paper · explained in 7 episodes
• Knowledge graphs — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Multi-objective Optimization — 1× in this paper · explained in 4 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Resource Constraints — 1× in this paper · explained in 3 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes

Sources

• Compression via Pre-trained Transformers: A Study on Byte-Level Multimodal Data
• An advantage actor-critic algorithm for robotic motion planning in dense and dynamic scenarios
• Recursive Least Squares Advantage Actor-Critic Algorithms
• Adam: A Method for Stochastic Optimization

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