From the 2 of 6 linked papers with an AI index.
6 papers
Sparse-LaViDa: Sparse Multimodal Discrete Diffusion Language Models
Shufan Li, Jiuxiang Gu, Kangning Liu +4
Masked Discrete Diffusion Models (MDMs) have achieved strong performance across a wide range of multimodal tasks, including image understanding, generation, and editing. However, t…
Lavida-O: Elastic Large Masked Diffusion Models for Unified Multimodal Understanding and Generation
Shufan Li, Jiuxiang Gu, Kangning Liu +4
Lavida-O is a unified masked diffusion model that combines a lightweight generation branch with a larger understanding branch to perform image understanding, object grounding, imag…
Diagnosing Training Inference Mismatch in LLM Reinforcement Learning
Tianle Zhong, Neiwen Ling, Yifan Pi +5
Modern LLM RL systems separate rollout generation from policy optimization. These two stages are expected to produce token probabilities that match exactly. However, implementation…
LPNSR: Optimal Noise-Guided Diffusion Image Super-Resolution Via Learnable Noise Prediction
Shuwei Huang, Shizhuo Liu, Zijun Wei
Diffusion-based image super-resolution (SR) aims to reconstruct high-resolution (HR) images from low-resolution (LR) observations. However, the inherent randomness injected during…
VGent: Visual Grounding via Modular Design for Disentangling Reasoning and Prediction
Weitai Kang, Jason Kuen, Mengwei Ren +3
Current visual grounding models are either based on a Multimodal Large Language Model (MLLM) that performs auto-regressive decoding, which is slow and risks hallucinations, or on r…
Refer to Any Segmentation Mask Group With Vision-Language Prompts
Shengcao Cao, Zijun Wei, Jason Kuen +6
Recent image segmentation models have advanced to segment images into high-quality masks for visual entities, and yet they cannot provide comprehensive semantic understanding for c…