1 citations · 1 across the 7 of their papers we have counts for
7 papers
Spherical Physics-informed Neural Operator with Multi-scale Coupling for Meteorological Downscaling
Yiqiang Ye, Yichi Wang, Haodi Zhang +5
Meteorological downscaling is crucial for high-resolution regional climate forecasting and disaster early warning. While neural operators have emerged as a promising paradigm for m…
Tyler: Typed Latent Reasoning for Language Models -- When to Think, What to Compute, and How Much to Allocate
Hanyu Lin, Min Cai, Jiawei Wen +1
Chain-of-thought (CoT) prompting improves reasoning in large language models (LLMs) by externalizing intermediate computation as discrete text tokens, but this textual interface al…
AudioCodecBench: A Comprehensive Benchmark for Audio Codec Evaluation
Lu Wang, Hao Chen, Siyu Wu +5
Multimodal Large Language Models (MLLMs) have been widely applied in speech and music. This tendency has led to a focus on audio tokenization for Large Models (LMs). Unlike semanti…
Towards Visualizing Electronic Medical Records via Natural Language Queries
Haodi Zhang, Siqi Ning, Qiyong Zheng +4
Electronic medical records (EMRs) contain essential data for patient care and clinical research. With the diversity of structured and unstructured data in EHR, data visualization i…
Towards Robustness of Text-to-Visualization Translation against Lexical and Phrasal Variability
Jinwei Lu, Yuanfeng Song, Haodi Zhang +2
Text-to-Vis is an emerging task in the natural language processing (NLP) area that aims to automatically generate data visualizations from natural language questions (NLQs). Despit…
Self-Convinced Prompting: Few-Shot Question Answering with Repeated Introspection
Haodi Zhang, Min Cai, Xinhe Zhang +3
While large language models (LLMs) such as ChatGPT and PaLM have demonstrated remarkable performance in various language understanding and generation tasks, their capabilities in c…
MMLN: Leveraging Domain Knowledge for Multimodal Diagnosis
Haodi Zhang, Chenyu Xu, Peirou Liang +4
Recent studies show that deep learning models achieve good performance on medical imaging tasks such as diagnosis prediction. Among the models, multimodality has been an emerging t…