14 papers
Beyond Perplexity: UTF-8 Validity in Byte-aware Language Models
Sangwhan Moon, Daisuke Oba, Youmi Ma +2
Byte-level tokenization enables language models to handle any Unicode input, but models can generate invalid UTF-8 sequences when encountering rare or unseen characters. We investi…
Neuron Level Analysis of Large Language Model in Legal Domain Reasoning
Eri Onami, Youmi Ma, Shuhei Kurita +1
We presented a neuron-level analysis of legal-domain reasoning in LLMs, comparing it with other applied domain tasks across seven open-weight models. Using neuron attribution score…
Autoregressive Direct Preference Optimization
Masanari Oi, Mahiro Ukai, Masahiro Kaneko +2
Direct preference optimization (DPO) has emerged as a promising approach for aligning large language models (LLMs) with human preferences. However, the widespread reliance on the r…
Aligning Tree-Search Policies with Fixed Token Budgets in Test-Time Scaling of LLMs
Sora Miyamoto, Daisuke Oba, Naoaki Okazaki
Tree-search decoding is an effective form of test-time scaling for large language models (LLMs), but real-world deployment often imposes a fixed per-query token budget that varies…
Drifting Objectives for Refining Discrete Diffusion Language Models
Daisuke Oba, Hiroki Furuta, Naoaki Okazaki
Discrete diffusion language models (DDLMs) generate text by iteratively denoising categorical token sequences, while recent drifting methods for continuous generators suggest that…
Diffusion-State Policy Optimization for Masked Diffusion Language Models
Daisuke Oba, Hiroki Furuta, Naoaki Okazaki
Masked diffusion language models generate text through iterative masked-token filling, but terminal-only rewards on final completions provide coarse credit assignment for the inter…