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cs.LG2026
From Drift to Coherence: Stabilizing Beliefs in LLMs
SongEun Kim, Seungyoo Lee, Edwin Fong +2
Large language models (LLMs) are often hypothesized to perform implicit Bayesian inference, yet a key coherence condition, the martingale property of predictive beliefs, has been s…
cs.CR2026
Parallel Test-Time Scaling with Multi-Sequence Verifiers
Yegon Kim, Seungyoo Lee, Chaeyun Jang +2
Parallel test-time scaling, which generates multiple candidate solutions for a single problem, is a powerful technique for improving large language model performance. However, it i…