4 citations · 17 across the 23 of their papers we have counts for
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cs.AI2026
Multi-LLM Collaborative Alignment via Stackelberg Games
Christina Hahn, Shangbin Feng, Dean Light +3
A pool of language models can collaborate and improve collectively by learning from one another's responses. These interactions depend on the instructions used during training. Exi…
cs.AI2026
Scaling Participation in Modular AI Systems
Shangbin Feng, Yike Wang, Weijia Shi +3
Humanity is a mosaic of multifaceted talents and needs, and any truly intelligent AI must reflect that richness. Yet the LLMs used by all are built by the few -- a centralized mark…
cs.AI2025
MMMG: a Comprehensive and Reliable Benchmark for Multitask Multimodal Generation
Jihan Yao, Yushi Hu, Yujie Yi +10
Automatically evaluating multimodal generation presents a significant challenge, as automated metrics often struggle to align with human evaluation, especially for complex tasks th…