Papers

• Preserving Privacy, Increasing Accessibility, and Reducing Cost: An On-Device Artificial Intelligence Model for Medical Transcription and Note Generation (2025)
  Johnson Thomas et al.
  2.87
• AVERE: Improving Audiovisual Emotion Reasoning with Preference Optimization (2026)
  Ashutosh Chaubey et al.
  1.94
• Trust Your Critic: Robust Reward Modeling and Reinforcement Learning for Faithful Image Editing and Generation (2026)
  Xiangyu Zhao et al.
  1.94
• Thinking in Uncertainty: Mitigating Hallucinations in MLRMs with Latent Entropy-Aware Decoding (2026)
  Zhongxing Xu et al.
  1.94
• Seeing Isn't Believing: Uncovering Blind Spots in Evaluator Vision-Language Models (2026)
  Mohammed Safi Ur Rahman Khan et al.
  1.94
• The First Token Knows: Single-Decode Confidence for Hallucination Detection (2026)
  Mina Gabriel
  1.89
• Reliable and Responsible Foundation Models: A Comprehensive Survey (2026)
  Xinyu Yang et al.
  1.72
• FilmAgent: A Multi-Agent Framework for End-to-End Film Automation in Virtual 3D Spaces (2025)
  Zhenran Xu et al.
  1.28
• Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generation (2025)
  Mohammad Mahdi Abootorabi et al.
  1.28
• Painting with Words: Elevating Detailed Image Captioning with Benchmark and Alignment Learning (2025)
  Qinghao Ye et al.
  1.28
• MIRIAD: Augmenting LLMs with millions of medical query-response pairs (2025)
  Qinyue Zheng et al.
  1.28
• LUMINA: Detecting Hallucinations in RAG System with Context-Knowledge Signals (2025)
  Min-Hsuan Yeh et al.
  1.28
• Training Language Models on the Knowledge Graph: Insights on Hallucinations and Their Detectability (2024)
  Jiri Hron et al.
  —
• xGen-MM (BLIP-3): A Family of Open Large Multimodal Models (2024)
  Le Xue et al.
  —
• The Curse of Multi-Modalities: Evaluating Hallucinations of Large Multimodal Models across Language, Visual, and Audio (2024)
  Sicong Leng et al.
  —