How Much Can Language Models Gain from Test-Time Computation?
cs.LG
Submitted: 2026-10-01
Updated: 2026-10-06
Sources
- Inference-Time Scaling for Complex Tasks: Where We Stand and What Lies Ahead
- Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
- Universal Self-Consistency for Large Language Model Generation
- Training Verifiers to Solve Math Word Problems
- Cost-of-Pass: An Economic Framework for Evaluating Language Models
- Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation
- Evaluating Test-Time Scaling of General LLM Agents
- Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces
- Kinetics: Rethinking Test-Time Scaling Laws
- When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning
- Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning
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