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Found 10 papers, 2 papers with code
M$^3$AV: A Multimodal, Multigenre, and Multipurpose Audio-Visual Academic Lecture Dataset
Although multiple academic video datasets have been constructed and released, few of them support both multimodal content recognition and understanding tasks, which is partially due to the lack of high-quality human annotations.
Automatic Interactive Evaluation for Large Language Models with State Aware Patient Simulator
Large Language Models (LLMs) have demonstrated remarkable proficiency in human interactions, yet their application within the medical field remains insufficiently explored.
M2K-VDG: Model-Adaptive Multimodal Knowledge Anchor Enhanced Video-grounded Dialogue Generation
Video-grounded dialogue generation (VDG) requires the system to generate a fluent and accurate answer based on multimodal knowledge.
MM-SAP: A Comprehensive Benchmark for Assessing Self-Awareness of Multimodal Large Language Models in Perception
We believe that these hallucinations are partially due to the models' struggle with understanding what they can and cannot perceive from images, a capability we refer to as self-awareness in perception.
New Sample Complexity Bounds for (Regularized) Sample Average Approximation in Several Heavy-Tailed, Non-Lipschitzian, and High-Dimensional Cases
In response, this paper presents three sets of results: First, we show that the (R)SAA is effective even if the objective function is not necessarily Lipschitz and the underlying distribution admits some bounded central moments only at (near-)optimal solutions.
MSG-BART: Multi-granularity Scene Graph-Enhanced Encoder-Decoder Language Model for Video-grounded Dialogue Generation
Generating dialogue grounded in videos requires a high level of understanding and reasoning about the visual scenes in the videos.
An Automatic Evaluation Framework for Multi-turn Medical Consultations Capabilities of Large Language Models
A medical consultation training set is further constructed to improve the consultation ability of LLMs.
A Dimension-Insensitive Algorithm for Stochastic Zeroth-Order Optimization
This paper concerns a convex, stochastic zeroth-order optimization (S-ZOO) problem.
Learnable Descent Algorithm for Nonsmooth Nonconvex Image Reconstruction
We propose a general learning based framework for solving nonsmooth and nonconvex image reconstruction problems.
A Novel Learnable Gradient Descent Type Algorithm for Non-convex Non-smooth Inverse Problems
Optimization algorithms for solving nonconvex inverse problem have attracted significant interests recently.
