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cs.CL2024
II-Bench: An Image Implication Understanding Benchmark for Multimodal Large Language Models
Ziqiang Liu, Feiteng Fang, Xi Feng +23
The rapid advancements in the development of multimodal large language models (MLLMs) have consistently led to new breakthroughs on various benchmarks. In response, numerous challe…
cs.CL2024
MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model Series
Ge Zhang, Scott Qu, Jiaheng Liu +42
Large Language Models (LLMs) have made great strides in recent years to achieve unprecedented performance across different tasks. However, due to commercial interest, the most comp…
cs.CL2023
Align on the Fly: Adapting Chatbot Behavior to Established Norms
Chunpu Xu, Steffi Chern, Ethan Chern +6
In this paper, we aim to align large language models with the ever-changing, complex, and diverse human values (e.g., social norms) across time and locations. This presents a chall…