Large Language Models are Approximate Survival Estimators

arXiv:2609.38181 · cs.CL · Submitted 2026-08-04 · Read on arXiv

cs.CL

Submitted: 2026-08-04

Updated: 2026-08-04

Terminology

• Calibration — 21× in this paper · explained in 7 episodes
• Accuracy — 17× in this paper · explained in 1 episode
• Ablation — 10× in this paper · explained in 1 episode
• Abstraction — 5× in this paper · explained in 1 episode
• Interpretability — 3× in this paper · explained in 15 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Explainability — 2× in this paper · explained in 3 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes

Sources

• Tx-LLM: A Large Language Model for Therapeutics
• Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale
• Language Models are Few-shot Learners for Prognostic Prediction
• Characterizing Delusional Spirals through Human-LLM Chat Logs
• Rethinking Interpretability in the Era of Large Language Models
• The Good, The Bad, and The Greedy: Evaluation of LLMs Should Not Ignore Non-Determinism
• OpenAI o1 System Card

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