Search Results for author:
Found 15 papers, 2 papers with code
MolGround: A Benchmark for Molecular Grounding
Current molecular understanding approaches predominantly focus on the descriptive aspect of human perception, providing broad, topic-level insights.
Mean of Means: Human Localization with Calibration-free and Unconstrained Camera Settings (extended version)
Accurate human localization is crucial for various applications, especially in the Metaverse era.
Generating on Generated: An Approach Towards Self-Evolving Diffusion Models
Recursive Self-Improvement (RSI) enables intelligence systems to autonomously refine their capabilities.
PolySmart and VIREO @ TRECVid 2024 Ad-hoc Video Search
The generated queries retrieve different rank lists from the original query.
PolySmart @ TRECVid 2024 Medical Video Question Answering
Specifically, we provide the video captions generated by the LLaVA-Next-Video model and the video subtitles with timestamps as context, and ask GPT4 to generate step captions for the given medical query.
PolySmart @ TRECVid 2024 Video Captioning (VTT)
In this paper, we present our methods and results for the Video-To-Text (VTT) task at TRECVid 2024, exploring the capabilities of Vision-Language Models (VLMs) like LLaVA and LLaVA-NeXT-Video in generating natural language descriptions for video content.
Multi-Level Querying using A Knowledge Pyramid
We propose a multi-layer knowledge pyramid approach within the RAG framework to achieve a better balance between precision and recall.
Mean of Means: A 10-dollar Solution for Human Localization with Calibration-free and Unconstrained Camera Settings
Accurate human localization is crucial for various applications, especially in the Metaverse era.
Uncertainty Estimation of Large Language Models in Medical Question Answering
In this work, we benchmark popular UE methods with different model sizes on medical question-answering datasets.
Improving Interpretable Embeddings for Ad-hoc Video Search with Generative Captions and Multi-word Concept Bank
Experimental results show that the integration of the above-proposed elements doubles the R@1 performance of the AVS method on the MSRVTT dataset and improves the xinfAP on the TRECVid AVS query sets for 2016-2023 (eight years) by a margin from 2% to 77%, with an average about 20%.
Interpretable Embedding for Ad-hoc Video Search
Answering query with semantic concepts has long been the mainstream approach for video search.
Reinforcement Learning Enhanced PicHunter for Interactive Search
With these improvements, the interactive system only searches a subset of video datasets relevant to a query while being able to quickly perform Bayesian updates with systematic planning to recommend the most probable candidates that can potentially lead to minimum iteration rounds.
Graph Learning based Generative Design for Resilience of Interdependent Network Systems
As for enhancing the designs, challenges have arisen for designing a robust system due to the increasing scale of modern systems and the complicated underlying physical constraints.
(Un)likelihood Training for Interpretable Embedding
Cross-modal representation learning has become a new normal for bridging the semantic gap between text and visual data.
Spectral Graph Clustering for Intentional Islanding Operations in Resilient Hybrid Energy Systems
Establishing cleaner energy generation therefore improving the sustainability of the power system is a crucial task in this century, and one of the key strategies being pursued is to shift the dependence on fossil fuel to renewable technologies such as wind, solar, and nuclear.
