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20232025
most citedEnhancing Multimodal Compositional Reasoning of Visual Language Models with Generative Negative Mining

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.NC2025

Bayes or Heisenberg: Who(se) Rules?

Volker Tresp, Hang Li, Federico Harjes +1

Although quantum systems are generally described by quantum state vectors, we show that in certain cases their measurement processes can be reformulated as probabilistic equations…

cs.LG2024

FedBiP: Heterogeneous One-Shot Federated Learning with Personalized Latent Diffusion Models

Haokun Chen, Hang Li, Yao Zhang +7

One-Shot Federated Learning (OSFL), a special decentralized machine learning paradigm, has recently gained significant attention. OSFL requires only a single round of client data o…

cs.AI2024

How the (Tensor-) Brain uses Embeddings and Embodiment to Encode Senses and Symbols

Volker Tresp, Hang Li

The Tensor Brain (TB) has been introduced as a computational model for perception and memory. This paper provides an overview of the TB model, incorporating recent developments and…

cs.CV2023★ 1 cited

Enhancing Multimodal Compositional Reasoning of Visual Language Models with Generative Negative Mining

Ugur Sahin, Hang Li, Qadeer Khan +2

Contemporary large-scale visual language models (VLMs) exhibit strong representation capacities, making them ubiquitous for enhancing image and text understanding tasks. They are o…

cs.CV2023★ 1 cited

Self-Discovering Interpretable Diffusion Latent Directions for Responsible Text-to-Image Generation

Hang Li, Chengzhi Shen, Philip Torr +2

Diffusion-based models have gained significant popularity for text-to-image generation due to their exceptional image-generation capabilities. A risk with these models is the poten…