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Large Vision-Language Models (LVLMs) exhibit powerful generative capabilities but frequently produce hallucinations that compromise output reliability. Fine tuning on annotated data devoid of hallucinations offers the most direct solution, while its high computational cost motivates recent repres...

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作者位次 #4/8KDD 2026Oral· Knowledge Discovery & Data Mining

Dynamic Spectral Denoising with Global-Context Attention for Multi-Behavior Recommendation

Miaomiao Cai · Yunshan Ma · Fangqi Zhu · Junfeng Fang · Zhijie Zhang · Zhiyong Cheng · Xiang Wang · See-Kiong Ng

检索与知识OpenReview

作者位次 #6/9KDD 2026Oral· Knowledge Discovery & Data Mining

Language-Enhanced Representation Learning for Single-Cell Transcriptomics

Jia-Qi Yang · ZHIYUAN LIU · Yaorui SHI · Qingchuan Zhang · Changhao Nai · Junfeng Fang · Yahui Long · Yang Zhang · Xiang Wang

可解释性检索与知识OpenReview

作者位次 #4/7AAAI 2026Poster· Artificial Intelligence

Hierarchical Semantic Alignment for Image Clustering

Xingyu Zhu · Beier Zhu · Yunfan Li · Junfeng Fang · Shuo Wang · Kesen Zhao · Hanwang Zhang

对齐与偏好多模态OpenReview

Junfeng Fang

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2026 顶会论文

Contrastive Weak-to-Strong Generalization

Enhancing Multi-Modal LLMs Reasoning via Difficulty-Aware Group Normalization

Revisiting Robustness for LLM Safety Alignment via Selective Geometry Control

R-Diverse: Mitigating Diversity Illusion in Self-Play LLM Training

NExT-Guard: Training-Free Streaming Safeguard without Token-Level Labels

See First, Reason Later: Mutual Information-Guided Reinforcement Learning for Vision-Language Models

AgentNoiseBench: Benchmarking Robustness of Tool-Using LLM Agents Under Noisy Condition

Temporal Self-Rewarding Language Models: Decoupling Chosen-Rejected via Past-Future

Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation

Dynamic Spectral Denoising with Global-Context Attention for Multi-Behavior Recommendation

Language-Enhanced Representation Learning for Single-Cell Transcriptomics

Hierarchical Semantic Alignment for Image Clustering

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