1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.AI2025
ContextNav: Towards Agentic Multimodal In-Context Learning
Honghao Fu, Yuan Ouyang, Kai-Wei Chang +3
Recent advances demonstrate that multimodal large language models (MLLMs) exhibit strong multimodal in-context learning (ICL) capabilities, enabling them to adapt to novel vision-l…
cs.CL2025
How to Make Large Language Models Generate 100% Valid Molecules?
Wen Tao, Jing Tang, Alvin Chan +5
Molecule generation is key to drug discovery and materials science, enabling the design of novel compounds with specific properties. Large language models (LLMs) can learn to perfo…
cs.CL2024★ 1 cited
Context-DPO: Aligning Language Models for Context-Faithfulness
Baolong Bi, Shaohan Huang, Yiwei Wang +11
Reliable responses from large language models (LLMs) require adherence to user instructions and retrieved information. While alignment techniques help LLMs align with human intenti…