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Sheng-hua Zhong

5 accepted papers

2026

From Pixels to Logic: A Perception-Reasoning Decomposition Framework for Open-World Referring Expression Comprehension

AAAI 2026technical

Recent advances in Referring Expression Comprehension (REC) have been largely driven by supervised learning on curated datasets, where each expression is assumed to refer to exactly one known object. However, such assumptions rarely hold in real-world scenarios, where expressions can refer to multip

Cited by 0SourcePDFScholar
2026

Is Symbolic Music a Specific Language? Exploring Inspiration-to-Structure Machine Composition via LLMs

AAAI 2026technical

Large Language Models (LLMs) have demonstrated remarkable proficiency in diverse tasks. This success raises a fundamental question in machine composition: Can symbolic music be considered a special form of language that can be jointly modeled with natural language for composition tasks? Recent studi

Cited by 0SourcePDFScholar
2025

Mixture of Knowledge Minigraph Agents for Literature Review Generation

AAAI 2025technical

Literature reviews play a crucial role in scientific research for understanding the current state of research, identifying gaps, and guiding future studies on specific topics. However, the process of conducting a comprehensive literature review is yet time-consuming. This paper proposes a novel fram…

Cited by 0SourcePDFScholar
2025

Towards General-Domain Word Sense Disambiguation: Distilling Large Language Model into Compact Disambiguator

EMNLP 2025

Word Sense Disambiguation (WSD) aims to determine the correct meaning of a word in context from a predefined inventory, and remains a fundamental challenge in natural language understanding. Existing methods rely heavily on manually annotated data, which limits coverage and generalization. In this w

2023

GLA-GCN: Global-local Adaptive Graph Convolutional Network for 3D Human Pose Estimation from Monocular Video

ICCV 2023poster

3D human pose estimation has been researched for decades with promising fruits. 3D human pose lifting is one of the promising research directions toward the task where both estimated pose and ground truth pose data are used for training. Existing pose lifting works mainly focus on improving the perf…

Cited by 80PDFcodeScholar