12 papers · 1 filter
Controlling Embedding Spaces with Text-Conditioned Transformations
Joseph Fioresi, Fabian Caba Heilbron, Pankaj Nathani +2
Multimodal embedding spaces in models like CLIP enable powerful capabilities such as semantic similarity retrieval and cross-modal zero-shot classification. These embeddings compre…
Seeing Through Words: Controlling Visual Retrieval Quality with Language Models
Jianglin Lu, Simon Jenni, Kushal Kafle +3
Text-to-image retrieval is a fundamental task in vision-language learning, yet in real-world scenarios it is often challenged by short and underspecified user queries. Such queries…
RetouchIQ: MLLM Agents for Instruction-Based Image Retouching with Generalist Reward
Qiucheng Wu, Jing Shi, Simon Jenni +4
Recent advances in multimodal large language models (MLLMs) have shown great potential for extending vision-language reasoning to professional tool-based image editing, enabling in…
More Than the Final Answer: Improving Visual Extraction and Logical Consistency in Vision-Language Models
Hoang Anh Just, Yifei Fan, Handong Zhao +6
Reinforcement learning from verifiable rewards (RLVR) has recently been extended from text-only LLMs to vision-language models (VLMs) to elicit long-chain multimodal reasoning. How…
Calibrating MLLM-as-a-judge via Multimodal Bayesian Prompt Ensembles
Eric Slyman, Mehrab Tanjim, Kushal Kafle +1
Multimodal large language models (MLLMs) are increasingly used to evaluate text-to-image (TTI) generation systems, providing automated judgments based on visual and textual context…
Plot'n Polish: Zero-shot Story Visualization and Disentangled Editing with Text-to-Image Diffusion Models
Kiymet Akdemir, Jing Shi, Kushal Kafle +2
Text-to-image diffusion models have demonstrated significant capabilities to generate diverse and detailed visuals in various domains, and story visualization is emerging as a part…