Summary of Enhancing Llm Safety Via Constrained Direct Preference Optimization, by Zixuan Liu et al.
Enhancing LLM Safety via Constrained Direct Preference Optimizationby Zixuan Liu, Xiaolin Sun, Zizhan ZhengFirst submitted…
Summary of What Do We Learn From Inverting Clip Models?, by Hamid Kazemi et al.
What do we learn from inverting CLIP models?by Hamid Kazemi, Atoosa Chegini, Jonas Geiping, Soheil…
Summary of Contrastive Region Guidance: Improving Grounding in Vision-language Models Without Training, by David Wan et al.
Contrastive Region Guidance: Improving Grounding in Vision-Language Models without Trainingby David Wan, Jaemin Cho, Elias…
Summary of Theoretical Insights For Diffusion Guidance: a Case Study For Gaussian Mixture Models, by Yuchen Wu et al.
Theoretical Insights for Diffusion Guidance: A Case Study for Gaussian Mixture Modelsby Yuchen Wu, Minshuo…
Summary of Pseudo-label Calibration Semi-supervised Multi-modal Entity Alignment, by Luyao Wang and Pengnian Qi and Xigang Bao and Chunlai Zhou and Biao Qin
Pseudo-Label Calibration Semi-supervised Multi-Modal Entity Alignmentby Luyao Wang, Pengnian Qi, Xigang Bao, Chunlai Zhou, Biao…
Summary of Pairwise Alignment Improves Graph Domain Adaptation, by Shikun Liu et al.
Pairwise Alignment Improves Graph Domain Adaptationby Shikun Liu, Deyu Zou, Han Zhao, Pan LiFirst submitted…
Summary of Deep Learning For Cross-domain Data Fusion in Urban Computing: Taxonomy, Advances, and Outlook, by Xingchen Zou et al.
Deep Learning for Cross-Domain Data Fusion in Urban Computing: Taxonomy, Advances, and Outlookby Xingchen Zou,…
Summary of Structure Preserving Diffusion Models, by Haoye Lu et al.
Structure Preserving Diffusion Modelsby Haoye Lu, Spencer Szabados, Yaoliang YuFirst submitted to arxiv on: 29…
Summary of Rethinking Multi-domain Generalization with a General Learning Objective, by Zhaorui Tan et al.
Rethinking Multi-domain Generalization with A General Learning Objectiveby Zhaorui Tan, Xi Yang, Kaizhu HuangFirst submitted…
Summary of Keeping Llms Aligned After Fine-tuning: the Crucial Role Of Prompt Templates, by Kaifeng Lyu et al.
Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templatesby Kaifeng Lyu, Haoyu Zhao,…