Where Do Test-Time Scaling and Training Fall Short in Individual Stance Prediction?

arXiv:2609.33155 · cs.CL · Submitted 2026-09-27 · Read on arXiv

cs.CL

Submitted: 2026-09-27

Updated: 2026-10-06

Terminology

• Accuracy — 24× in this paper · explained in 1 episode
• Adaptation — 15× in this paper · explained in 1 episode
• GRPO — 13× in this paper · explained in 6 episodes
• Steering — 12× in this paper · explained in 2 episodes
• Test-time Scaling — 12× in this paper · explained in 2 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Consistency — 7× in this paper · explained in 3 episodes
• Failure Modes — 7× in this paper · explained in 3 episodes
• Self-consistency — 7× in this paper · explained in 2 episodes
• Reinforcement Learning — 6× in this paper · explained in 4 episodes
• Verifier — 6× in this paper · explained in 2 episodes
• Benchmark — 5× in this paper · explained in 2 episodes
• Fine-Tuning — 5× in this paper · explained in 5 episodes
• Frozen model — 4× in this paper · explained in 3 episodes
• LoRA Adapters — 3× in this paper · explained in 3 episodes
• F1 Score — 2× in this paper · explained in 3 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• Personalization — 2× in this paper · explained in 2 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Agent-based modeling — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 4 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• KL Regularization — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Mode Collapse — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Test-Time Scaling (TTS) — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• CodeT: Code Generation with Generated Tests
• Universal Self-Consistency for Large Language Model Generation
• When Synthetic Users Fail: A Cross-Domain Benchmark of LLM-Simulated Human Survey Responses
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• HumanStudy-Bench: Towards AI Agent Design for Participant Simulation
• Predicting User Stances from Target-Agnostic Information using Large Language Models
• LLM Agents Grounded in Self-Reports Enable General-Purpose Simulation of Individuals
• Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity

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