Search Results for author:
Found 7 papers, 4 papers with code
Dual-Perspective Knowledge Enrichment for Semi-Supervised 3D Object Detection
Our DPKE enriches the knowledge of limited training data, particularly unlabeled data, from two perspectives: data-perspective and feature-perspective.
AppAgent: Multimodal Agents as Smartphone Users
Recent advancements in large language models (LLMs) have led to the creation of intelligent agents capable of performing complex tasks.
ICD-LM: Configuring Vision-Language In-Context Demonstrations by Language Modeling
Moreover, during data construction, we use the LVLM intended for ICL implementation to validate the strength of each ICD sequence, resulting in a model-specific dataset and the ICD-LM trained by this dataset is also model-specific.
ChartLlama: A Multimodal LLM for Chart Understanding and Generation
Next, we introduce ChartLlama, a multi-modal large language model that we've trained using our created dataset.
Prompt-aligned Gradient for Prompt Tuning
Thanks to the large pre-trained vision-language models (VLMs) like CLIP, we can craft a zero-shot classifier by "prompt", e. g., the confidence score of an image being "[CLASS]" can be obtained by using the VLM provided similarity measure between the image and the prompt sentence "a photo of a [CLASS]".
Fast AdvProp
Specifically, our modifications in Fast AdvProp are guided by the hypothesis that disentangled learning with adversarial examples is the key for performance improvements, while other training recipes (e. g., paired clean and adversarial training samples, multi-step adversarial attackers) could be largely simplified.
Relational Reasoning Over Spatial-Temporal Graphs for Video Summarization
Then, we construct a temporal graph by using the aggregated representations of spatial graphs.
Ranked #1 on
Video Summarization
on TvSum
(using extra training data)
