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Jiaming Huang

7 accepted papers

2026

RAG-R1:Incentivizing the Search and Reasoning Capabilities of LLMs Through Multi-Query Parallelism

AAAI 2026technical

Large Language Models (LLMs), despite their remarkable capabilities, are prone to generating hallucinated or outdated content due to their static internal knowledge. While Retrieval-Augmented Generation (RAG) integrated with Reinforcement Learning (RL) offers a solution, these methods are fundament

Cited by 0SourcePDFScholar
2026

SemanticNN: Compressive and Error-Resilient Semantic Offloading for Extremely Weak Devices

AAAI 2026technical

With the rapid growth of the Internet of Things (IoT), integrating artificial intelligence (AI) on extremely weak embedded devices has garnered significant attention, enabling improved real-time performance and enhanced data privacy. However, the resource limitations of such devices and unreliable n

Cited by 0SourcePDFScholar
2026

SimpleDiffusion: A Lightweight and Efficient Conditional Diffusion Model for Multi-Modal Salient Object Detection

AAAI 2026technical

Multi-modal salient object detection (MSOD), which integrates complementary modalities such as depth or thermal data, primarily faces two challenges: accurately preserving salient object details and effectively aligning cross-modal features. Recent advances in using Stable Diffusion to generate imag

Cited by 0SourcePDFScholar
2025

DiMSOD: A Diffusion-Based Framework for Multi-Modal Salient Object Detection

AAAI 2025technical

Multi-modal salient object detection (SOD) through the integration of additional data such as depth or thermal information has become a significant task in computer vision during recent years. Traditionally, the challenges of identifying salient objects in RGB, RGB-D (Depth), and RGB-T (Thermal) ima…

Cited by 0SourcePDFScholar
2025

Multi-modal Salient Object Detection via a Unified Diffusion Model

ICASSP 2025accepted

Salient Object Detection (SOD) aims to identify and segment the most striking elements within an image. Salient object detection methods can be differentiated into several types according to the input data, such as RGB-D (Depth) and RGB-T (Thermal). Previous research primarily focused on saliency de…

Cited by 0SourceScholar
2025

Seg-diffusion: Text-to-Image Diffusion Model for Open-Vocabulary Semantic Segmentation

ICASSP 2025accepted

Open-vocabulary semantic segmentation (OVSS) is a challenging computer vision task that labels each pixel within an image based on text descriptions. Recent advancements in OVSS are largely attributed to the increased model capacity. However, these models often struggle with unfamiliar images or uns…

Cited by 0SourceScholar
2020

Collaboration Based Multi-Label Propagation for Fraud Detection

IJCAI 2020poster

Detecting fraud users, who fraudulently promote certain target items, is a challenging issue faced by e-commerce platforms. Generally, many fraud users have different spam behaviors simultaneously, e.g. spam transactions, clicks, reviews and so on. Existing solutions have two main limitations: 1) th…

Cited by 0SourcePDFScholar