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Yiming Tang

7 accepted papers

2026

FreDN: Spectral Disentanglement for Time Series Forecasting via Learnable Frequency Decomposition

AAAI 2026technical

Time series forecasting is essential in a wide range of real world applications. Recently, frequency-domain methods have attracted increasing interest for their ability to capture global dependencies. However, when applied to non-stationary time series, these methods encounter the spectral entanglem

Cited by 0SourcePDFScholar
2026

FunCQNet: A Functional Censored Quantile Neural Network for Predicting Long-Term Post-Transplant Kidney Survival

ICML 2026poster

Accurate survival prediction in kidney transplantation is critical yet challenging due to the complex interplay between functional biomarkers and patient characteristics under censoring. To address this, we propose a functional censored quantile neural network (FunCQNet), a novel framework that inte…

Cited by 0SourceScholar
2025

DaNet: Dual-Aware Enhanced Alignment Network for Multimodal Aspect-Based Sentiment Analysis

ACL 2025finding

Multimodal Aspect-Based Sentiment Analysis (MABSA) aims to extract aspect-sentiment pairs from text and image data. While significant progress has been made in image-aspect alignment, due to the subtlety and complexity of language expressions, there are not always explicit aspect words in the langua…

Cited by 0SourcePDFScholar
2025

Multimodal Invariant Sentiment Representation Learning

ACL 2025finding

Multimodal Sentiment Analysis (MSA) integrates diverse modalities to overcome the limitations of unimodal data. However, existing MSA datasets commonly exhibit significant sentiment distribution imbalances and cross-modal sentiment conflicts, which hinder performance improvement. This paper shows th…

2025

Proxy-Driven Robust Multimodal Sentiment Analysis with Incomplete Data

ACL 2025long

Multimodal Sentiment Analysis (MSA) with incomplete data has gained significant attention recently. Existing studies focus on optimizing model structures to handle modality missingness, but models still face challenges in robustness when dealing with uncertain missingness. To this end, we propose a…

2025

SAN: Hypothesizing Long-Term Synaptic Development and Neural Engram Mechanism in Scalable Model's Parameter-Efficient Fine-Tuning

ICML 2025poster

Advances in Parameter-efficient Fine-tuning (PEFT) bridged the performance gap with Full Fine-Tuning (FFT) through sophisticated analysis of pre-trained parameter spaces. Starting from drawing insights from Neural Engrams (NE) in Biological Neural Networks (BNNs), we establish a connection between t…

2024

LLM as Dataset Analyst: Subpopulation Structure Discovery with Large Language Model

ECCV 2024poster

"The distribution of subpopulations is an important property hidden within a dataset. Uncovering and analyzing the subpopulation distribution within datasets provides a comprehensive understanding of the datasets, standing as a powerful tool beneficial to various downstream tasks, including Dataset…