7 citations · 8 across the 10 of their papers we have counts for
4 papers · 1 filter
Narrative Flattening: How Post-Training Compresses Thematic, Affective, and Stylistic Variation in LLM Fiction
Zehan Li, Yutong Zhu, Siyang Wu +2
Large language models produce fluent fiction, yet their creative output is widely seen as flat. We ask where this quality originates in the training and whether it affects differen…
The MiniMax-M2 Series: Mini Activations Unleashing Max Real-World Intelligence
Aili Chen, Aonian Li, Baichuan Zhou +215
We introduce the MiniMax-M2 series, a family of Mixture-of-Experts language models built around the principle that mini activations can unleash maximum real-world intelligence. The…
Audio-Cogito: Towards Deep Audio Reasoning in Large Audio Language Models
Longhao Li, Hongjie Chen, Zehan Li +5
Recent advances in reasoning models have driven significant progress in text and multimodal domains, yet audio reasoning remains relatively limited. Only a few Large Audio Language…
A Unified Spoken Language Model with Injected Emotional-Attribution Thinking for Human-like Interaction
Qing Wang, Zehan Li, Yaodong Song +6
This paper presents a unified spoken language model for emotional intelligence, enhanced by a novel data construction strategy termed Injected Emotional-Attribution Thinking (IEAT)…