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20242026
most citedRLAIF-V: Open-Source AI Feedback Leads to Super GPT-4V Trustworthiness

3 citations · 4 across the 9 of their papers we have counts for

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cs.CL2026

Beyond Overlap Metrics: Rewarding Reasoning and Preferences for Faithful Multi-Role Dialogue Summarization

Xiaoyong Mei, Tingting Zuo, Da Chen +5

Multi-role dialogue summarization requires modeling complex interactions among multiple speakers while preserving role-specific information and factual consistency. However, most e…

cs.CL2025

ExPO-HM: Learning to Explain-then-Detect for Hateful Meme Detection

Jingbiao Mei, Mingsheng Sun, Jinghong Chen +4

Hateful memes have emerged as a particularly challenging form of online abuse, motivating the development of automated detection systems. Most prior approaches rely on direct detec…

cs.CL2025

MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention

MiniMax, :, Aili Chen +125

We introduce MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model. MiniMax-M1 is powered by a hybrid Mixture-of-Experts (MoE) architecture combin…

cs.CL2025★ 1 cited

MiniMax-01: Scaling Foundation Models with Lightning Attention

MiniMax, Aonian Li, Bangwei Gong +87

We introduce MiniMax-01 series, including MiniMax-Text-01 and MiniMax-VL-01, which are comparable to top-tier models while offering superior capabilities in processing longer conte…

cs.CL2024★ 3 cited

RLAIF-V: Open-Source AI Feedback Leads to Super GPT-4V Trustworthiness

Tianyu Yu, Haoye Zhang, Qiming Li +13

Traditional feedback learning for hallucination reduction relies on labor-intensive manual labeling or expensive proprietary models. This leaves the community without foundational…