2 papers
cs.CL2026
Evaluating LLMs' Divergent Thinking Capabilities for Scientific Idea Generation with Minimal Context
Kai Ruan, Xuan Wang, Jixiang Hong +3
While Large Language Models (LLMs) demonstrate remarkable capabilities in scientific tasks such as literature analysis and experimental design (e.g., accurately extracting key find…
cs.AI2025
SUDER: Self-Improving Unified Large Multimodal Models for Understanding and Generation with Dual Self-Rewards
Jixiang Hong, Yiran Zhang, Guanzhong Wang +3
Building upon large language models (LLMs), recent large multimodal models (LMMs) unify cross-model understanding and generation into a single framework. However, LMMs still strugg…