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AAAI 2025

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AntTech
AntTech
Mar 10, 2025 · Artificial Intelligence

Ant Insurance and Zhejiang University’s AAAI 2025 Papers Tackle Hallucination in Large Vision‑Language and Video Models

Two collaborative papers by Ant Insurance and Zhejiang University were accepted at AAAI 2025, introducing the MoLE decoding framework to reduce hallucination in large vision‑language models and the MHBench benchmark plus Motion Contrastive Decoding to address motion hallucination in video large language models, advancing reliable AI‑driven insurance claim processing.

AAAI 2025AI researchhallucination
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Ant Insurance and Zhejiang University’s AAAI 2025 Papers Tackle Hallucination in Large Vision‑Language and Video Models
AntTech
AntTech
Feb 26, 2025 · Artificial Intelligence

Ant Group’s 18 Accepted Papers at AAAI 2025: Summaries and Highlights

This article presents concise English summaries of the 18 Ant Group papers accepted at AAAI 2025, covering topics such as privacy‑preserving large‑model tuning, knowledge‑graph integration, AI‑generated image detection, multi‑task learning, generative retrieval, role‑playing evaluation, and video hallucination mitigation.

AAAI 2025AI evaluationVideo Hallucination
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Ant Group’s 18 Accepted Papers at AAAI 2025: Summaries and Highlights
Kuaishou Tech
Kuaishou Tech
Jan 17, 2025 · Artificial Intelligence

Kuaishou Achieves 7 Papers Accepted at AAAI 2025

Kuaishou has achieved a significant milestone with 7 papers accepted at AAAI 2025, covering diverse AI research areas including video processing, recommendation systems, and image restoration, demonstrating the company's strong research capabilities in artificial intelligence.

AAAI 2025Artificial IntelligenceKuaishou
0 likes · 10 min read
Kuaishou Achieves 7 Papers Accepted at AAAI 2025
AntTech
AntTech
Jan 13, 2025 · Artificial Intelligence

Two Ant Group Papers Selected for AAAI 2025: Human‑Feedback Evaluation Framework for Product Image Background Inpainting and Bagging‑Expert Network for Multi‑Task Learning

Two Ant Group papers accepted at AAAI 2025—one presenting a human‑feedback‑driven evaluation framework for product image background inpainting using EfficientSAM and a new HFPC‑44k dataset, and the other proposing a Bagging‑Expert Network to mitigate expert polarization in multi‑gate mixture‑of‑experts for multi‑task learning.

AAAI 2025Ant GroupBagging-Expert Network
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Two Ant Group Papers Selected for AAAI 2025: Human‑Feedback Evaluation Framework for Product Image Background Inpainting and Bagging‑Expert Network for Multi‑Task Learning