3 citations · 6 across the 15 of their papers we have counts for
7 papers · 1 filter
Drawing the Line: Enhancing Trustworthiness of MLLMs Through the Power of Refusal
Yuhao Wang, Zhiyuan Zhu, Heyang Liu +4
Multimodal large language models (MLLMs) excel at multimodal perception and understanding, yet their tendency to generate hallucinated or inaccurate responses undermines their trus…
Med-PMC: Medical Personalized Multi-modal Consultation with a Proactive Ask-First-Observe-Next Paradigm
Hongcheng Liu, Yusheng Liao, Siqv Ou +4
The application of the Multi-modal Large Language Models (MLLMs) in medical clinical scenarios remains underexplored. Previous benchmarks only focus on the capacity of the MLLMs in…
Decoding Linguistic Representations of Human Brain
Yu Wang, Heyang Liu, Yuhao Wang +6
Language, as an information medium created by advanced organisms, has always been a concern of neuroscience regarding how it is represented in the brain. Decoding linguistic repres…
Towards an End-to-End Framework for Invasive Brain Signal Decoding with Large Language Models
Sheng Feng, Heyang Liu, Yu Wang +1
In this paper, we introduce a groundbreaking end-to-end (E2E) framework for decoding invasive brain signals, marking a significant advancement in the field of speech neuroprosthesi…
MAV: A Multimodal, Multigenre, and Multipurpose Audio-Visual Academic Lecture Dataset
Zhe Chen, Heyang Liu, Wenyi Yu +6
Publishing open-source academic video recordings is an emergent and prevalent approach to sharing knowledge online. Such videos carry rich multimodal information including speech,…
Post-decoder Biasing for End-to-End Speech Recognition of Multi-turn Medical Interview
Heyang Liu, Yu Wang, Yanfeng Wang
End-to-end (E2E) approach is gradually replacing hybrid models for automatic speech recognition (ASR) tasks. However, the optimization of E2E models lacks an intuitive method for h…
MM-SAP: A Comprehensive Benchmark for Assessing Self-Awareness of Multimodal Large Language Models in Perception
Yuhao Wang, Yusheng Liao, Heyang Liu +3
Recent advancements in Multimodal Large Language Models (MLLMs) have demonstrated exceptional capabilities in visual perception and understanding. However, these models also suffer…