2 citations · 4 across the 18 of their papers we have counts for
6 papers · 1 filter
Is Text All You Need? Text as a Universal Information Bottleneck for Speech LLMs
Ming-Hao Hsu, Yuxuan Hu, Shujie Liu +3
Large language models (LLMs) provide a powerful reasoning backbone for speech understanding, but integrating continuous acoustic signals into a pretrained LLM remains challenging.…
A Decade-Scale Benchmark Evaluating LLMs' Clinical Practice Guidelines Detection and Adherence in Multi-turn Conversations
Andong Tan, Shuyu Dai, Jinglu Wang +7
Clinical practice guidelines (CPGs) play a pivotal role in ensuring evidence-based decision-making and improving patient outcomes. While Large Language Models (LLMs) are increasing…
Closing the Modality Reasoning Gap for Speech Large Language Models
Chaoren Wang, Heng Lu, Xueyao Zhang +4
Although Speech Large Language Models have achieved notable progress, a substantial modality reasoning gap remains: their reasoning performance on speech inputs is markedly weaker…
AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Construction
Hong Ting Tsang, Jiaxin Bai, Haoyu Huang +5
Building effective knowledge graphs (KGs) for Retrieval-Augmented Generation (RAG) is pivotal for advancing question answering (QA) systems. However, its effectiveness is hindered…
TrInk: Ink Generation with Transformer Network
Zezhong Jin, Shubhang Desai, Xu Chen +8
In this paper, we propose TrInk, a Transformer-based model for ink generation, which effectively captures global dependencies. To better facilitate the alignment between the input…
FELLE: Autoregressive Speech Synthesis with Token-Wise Coarse-to-Fine Flow Matching
Hui Wang, Shujie Liu, Lingwei Meng +9
To advance continuous-valued token modeling and temporal-coherence enforcement, we propose FELLE, an autoregressive model that integrates language modeling with token-wise flow mat…