2 papers
q-bio.GN2026
Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer
Yanan Li, Christina Yi Jin, Yuan Jin +5
A central challenge in developing Multimodal Large Language Models (MLLMs) is effectively integrating heterogeneous inputs into a cohesive reasoning engine. Current paradigms predo…
cs.CL2026
DESIGNER: Design-Logic-Guided Multidisciplinary Data Synthesis for LLM Reasoning
Weize Liu, Yongchi Zhao, Yijia Luo +8
Large language models (LLMs) perform strongly on many language tasks but still struggle with complex multi-step reasoning across disciplines. Existing reasoning datasets often lack…