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20232026
most citedSelfEvolve: A Code Evolution Framework via Large Language Models

18 citations · 23 across the 14 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CL2024

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…

cs.CL2024★ 1 cited

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…

cs.CL2024

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…

cs.CL2024★ 3 cited

Automatic Interactive Evaluation for Large Language Models with State Aware Patient Simulator

Yusheng Liao, Yutong Meng, Yuhao Wang +3

Large Language Models (LLMs) have demonstrated remarkable proficiency in human interactions, yet their application within the medical field remains insufficiently explored. Previou…

cs.CV2024

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…