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20212026
most citedUncertainty-Aware Model Adaptation for Unsupervised Cross-Domain Object Detection

3 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

TextBFGS: A Case-Based Reasoning Approach to Code Optimization via Error-Operator Retrieval

Zizheng Zhang, Yuyang Liao, Chen Chen +8

Iterative code generation with Large Language Models (LLMs) can be viewed as an optimization process guided by textual feedback. However, existing LLM self-correction methods predo…

cs.SD2025

UniArray: Unified Spectral-Spatial Modeling for Array-Geometry-Agnostic Speech Separation

Weiguang Chen, Junjie Zhang, Jielong Yang +2

Array-geometry-agnostic speech separation (AGA-SS) aims to develop an effective separation method regardless of the microphone array geometry. Conventional methods rely on permutat…

cs.LG2023

FRGNN: Mitigating the Impact of Distribution Shift on Graph Neural Networks via Test-Time Feature Reconstruction

Rui Ding, Jielong Yang, Feng Ji +2

Due to inappropriate sample selection and limited training data, a distribution shift often exists between the training and test sets. This shift can adversely affect the test perf…

eess.AS2023★ 1 cited

Unifying Speech Enhancement and Separation with Gradient Modulation for End-to-End Noise-Robust Speech Separation

Yuchen Hu, Chen Chen, Heqing Zou +2

Recent studies in neural network-based monaural speech separation (SS) have achieved a remarkable success thanks to increasing ability of long sequence modeling. However, they woul…

cs.CV2021★ 3 cited

Uncertainty-Aware Model Adaptation for Unsupervised Cross-Domain Object Detection

Minjie Cai, Minyi Luo, Xionghu Zhong +1

This work tackles the unsupervised cross-domain object detection problem which aims to generalize a pre-trained object detector to a new target domain without labels. We propose an…