1 citations · 1 across the 9 of their papers we have counts for
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FreeFuse: Multi-Subject LoRA Fusion via Adaptive Token-Level Routing at Test Time
Yaoli Liu, Yao-Xiang Ding, Kun Zhou
This paper proposes FreeFuse, a training-free framework for multi-subject text-to-image generation through automatic fusion of multiple subject LoRAs. In contrast to prior studies…
Abductive Logical Rule Induction by Bridging Inductive Logic Programming and Multimodal Large Language Models
Yifei Peng, Yaoli Liu, Enbo Xia +5
We propose ILP-CoT, a method that bridges Inductive Logic Programming (ILP) and Multimodal Large Language Models (MLLMs) for abductive logical rule induction. The task involves bot…
ROVI: A VLM-LLM Re-Captioned Dataset for Open-Vocabulary Instance-Grounded Text-to-Image Generation
Cihang Peng, Qiming Hou, Zhong Ren +1
We present ROVI, a high-quality synthetic dataset for instance-grounded text-to-image generation, created by labeling 1M curated web images. Our key innovation is a strategy called…
Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation
Jingming Liu, Yumeng Li, Wei Shi +3
Recent studies have proposed leveraging Large Language Models (LLMs) as information retrievers through query rewriting. However, for challenging corpora, we argue that enhancing qu…
Pre-Training Meta-Rule Selection Policy for Visual Generative Abductive Learning
Yu Jin, Jingming Liu, Zhexu Luo +5
Visual generative abductive learning studies jointly training symbol-grounded neural visual generator and inducing logic rules from data, such that after learning, the visual gener…