103 citations · 187 across the 25 of their papers we have counts for
9 papers · 1 filter
BCT: Bayes-Consistent Tempering for Flow Language Models
Daisuke Oba, Hiroki Furuta, Naoaki Okazaki
Temperature scaling is typically applied as a post-hoc transformation of model probabilities. In posterior-induced flow language models, this creates two mismatches. First, posteri…
Matching Object or Relation? Tracing Abstract Reasoning Inside VLMs
Gouki Minegishi, Hiroki Furuta, Takeshi Kojima +2
Vision Language Models (VLMs) excel on visual benchmarks but fail systematically on tasks requiring abstract reasoning. Existing benchmarks document this failure but cannot say \em…
VIF-Bench: Evaluating Visual Instruction Following in Multi-Reference Image Generation
Yuta Oshima, Masakazu Yoshimura, Masahiro Suzuki +2
Recent multimodal image generation models can take multiple images and textual instructions as input, enabling reference-based generation guided not only by text but also by visual…
AutoRef: Harness Optimization for Agentic Multi-Reference Image Generation
Yuta Oshima, Ku Onoda, Yusuke Iwasawa +3
Recent image generation models can take multiple reference images as input and combine them into a new image. However, multi-reference image generation remains challenging: models…
Multi-Axis Max@K Reinforcement Learning for Representative Diversity in Text-to-Image Generation
Ku Onoda, Paavo Parmas, Hiroki Furuta +4
Text-to-image (T2I) models can synthesize realistic, prompt-aligned images, yet samples generated for the same prompt often cover only a small subset of visually distinct modes. Th…
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…
Understanding Emergent Misalignment via Feature Superposition Geometry
Gouki Minegishi, Hiroki Furuta, Takeshi Kojima +2
Emergent misalignment, where fine-tuning on narrow, non-harmful tasks induces harmful behaviors, poses a key challenge for AI safety in LLMs. Despite growing empirical evidence, it…
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…
Emergent Analogical Reasoning in Transformers
Gouki Minegishi, Jingyuan Feng, Hiroki Furuta +3
Analogy is a central faculty of human intelligence, enabling abstract patterns discovered in one domain to be applied to another. Despite its central role in cognition, the mechani…