7 citations · 8 across the 10 of their papers we have counts for
5 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…
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)…
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…