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20242026
most citedHybrid Classification-Regression Adaptive Loss for Dense Object Detection

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2026

SMADE-IE: Sparse Multi-Agent Framework with Evidence-Driven Debate for Zero-Shot Information Extraction

Kenfeng Huang, Yi Cai, Xin Wu +2

Zero-shot information extraction (IE) with large language models (LLMs) has attracted increasing attention due to its flexibility in adapting to new schemas and domains without tas…

cs.AI2025

Hybrid-DMKG: A Hybrid Reasoning Framework over Dynamic Multimodal Knowledge Graphs for Multimodal Multihop QA with Knowledge Editing

Li Yuan, Qingfei Huang, Bingshan Zhu +5

Multimodal Knowledge Editing (MKE) extends traditional knowledge editing to settings involving both textual and visual modalities. However, existing MKE benchmarks primarily assess…

cs.CV2025

CADReview: Automatically Reviewing CAD Programs with Error Detection and Correction

Jiali Chen, Xusen Hei, HongFei Liu +5

Computer-aided design (CAD) is crucial in prototyping 3D objects through geometric instructions (i.e., CAD programs). In practical design workflows, designers often engage in time-…

cs.LG2025

Collaborative Multi-LoRA Experts with Achievement-based Multi-Tasks Loss for Unified Multimodal Information Extraction

Li Yuan, Yi Cai, Xudong Shen +4

Multimodal Information Extraction (MIE) has gained attention for extracting structured information from multimedia sources. Traditional methods tackle MIE tasks separately, missing…

cs.CV20242 cited

Hybrid Classification-Regression Adaptive Loss for Dense Object Detection

Yanquan Huang, Liu Wei Zhen, Yun Hao +5

For object detection detectors, enhancing model performance hinges on the ability to simultaneously consider inconsistencies across tasks and focus on difficult-to-train samples. A…