7 citations · 8 across the 10 of their papers we have counts for
10 papers
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)…
Multilingual Speech Recognition Using Discrete Tokens with a Two-step Training Strategy
Zehan Li, Yan Yang, Xueqing Li +3
Pre-trained models, especially self-supervised learning (SSL) models, have demonstrated impressive results in automatic speech recognition (ASR) task. While most applications of SS…
GOAT-SLM: A Spoken Language Model with Paralinguistic and Speaker Characteristic Awareness
Hongjie Chen, Zehan Li, Yaodong Song +13
Recent advances in end-to-end spoken language models (SLMs) have significantly improved the ability of AI systems to engage in natural spoken interactions. However, most existing m…
TELEVAL: A Benchmark Designed for Spoken Language Models in Chinese Interactive Scenarios
Zehan Li, Hongjie Chen, Qing Wang +9
Spoken Language Models (SLMs) are expected to support natural spoken interaction beyond task completion. However, existing SLM benchmarks primarily evaluate semantic correctness in…
GOAT-TTS: Expressive and Realistic Speech Generation via A Dual-Branch LLM
Yaodong Song, Hongjie Chen, Jie Lian +8
While large language models (LLMs) have revolutionized text-to-speech (TTS) synthesis through discrete tokenization paradigms, current architectures exhibit fundamental tensions be…
Bridging the Gap between Continuous and Informative Discrete Representations by Random Product Quantization
Xueqing Li, Hao Ma, Zehan Li +8
Self-supervised learning (SSL) has become a core technique in speech processing, but the high dimensionality of its representations makes discretization essential for improving eff…
Advancing GenAI Assisted Programming--A Comparative Study on Prompt Efficiency and Code Quality Between GPT-4 and GLM-4
Angus Yang, Zehan Li, Jie Li
This study aims to explore the best practices for utilizing GenAI as a programming tool, through a comparative analysis between GPT-4 and GLM-4. By evaluating prompting strategies…