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Found 6 papers, 5 papers with code
VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models
Based on the evaluation results obtained with the toolkit, we host OpenVLM Leaderboard, a comprehensive leaderboard to track the progress of multi-modality learning research.
Prism: A Framework for Decoupling and Assessing the Capabilities of VLMs
Vision Language Models (VLMs) demonstrate remarkable proficiency in addressing a wide array of visual questions, which requires strong perception and reasoning faculties.
CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs
When exploring the development of Artificial General Intelligence (AGI), a critical task for these models involves interpreting and processing information from multiple image inputs.
Ranked #4 on
Visual Reasoning
on Winoground
Model-based Offline Policy Optimization with Adversarial Network
Model-based offline reinforcement learning (RL), which builds a supervised transition model with logging dataset to avoid costly interactions with the online environment, has been a promising approach for offline policy optimization.
Making Offline RL Online: Collaborative World Models for Offline Visual Reinforcement Learning
Training offline RL models using visual inputs poses two significant challenges, i. e., the overfitting problem in representation learning and the overestimation bias for expected future rewards.
Deep Learning for Stock Selection Based on High Frequency Price-Volume Data
Training a practical and effective model for stock selection has been a greatly concerned problem in the field of artificial intelligence.
