Delayed Supervision for Test-Time Language Models

arXiv:2609.32312 · cs.AI · Submitted 2026-09-26 · Read on arXiv

cs.AI

Submitted: 2026-09-26

Updated: 2026-09-26

Terminology

• Benchmark — 16× in this paper · explained in 2 episodes
• Adaptation — 4× in this paper · explained in 1 episode
• Transformer — 4× in this paper · explained in 2 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Provenance — 2× in this paper · explained in 4 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• TextWorld: A Learning Environment for Text-based Games
• RULER: What's the Real Context Size of Your Long-Context Language Models?
• Reinforced Fast Weights with Next-Sequence Prediction
• Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention
• RWKV-7 "Goose" with Expressive Dynamic State Evolution
• Learning to (Learn at Test Time): RNNs with Expressive Hidden States
• Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks
• Parallelizing Linear Transformers with the Delta Rule over Sequence Length
• Test-Time Training Done Right

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