Michael Cogswell
10 papers · 2016–2025 · 7 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (23) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
🧬
Topic Evolution
🧭
Keyword Pioneer
📈
Trend Setter
🗃️
Keyword Collector
(56)
💎
Century Club · Bronze
Top co-authors
Research topics
Artificial Intelligence
(6)
Core AI
(6)
Machine Learning
(4)
Learning Types · Machine Learning
(4)
Deep Learning
(3)
Natural Language Processing
(3)
Applications
(2)
Architectures
(2)
Learning Types · Deep Learning
(2)
Computer Vision
(1)
Reinforcement Learning
(1)
Analysis
(1)
Core Methods
(1)
Generation
(1)
Methods
(1)
Keywords
large vision-language model
(2)
visual question answering
(2)
zero-shot learning
(2)
ensemble learning
(1)
vision-language alignment
(1)
video retrieval
(1)
domain adaptation
(1)
question answering
(1)
chain-of-thought reasoning
(1)
multimodal learning
(1)
visual dialog
(1)
video understanding
(1)
temporal reasoning
(1)
visual dialog agents
(1)
benchmark evaluation
(1)
synthetic data generation
(1)
multiple choice learning
(1)
backdoor attack
(1)
vision-language model
(1)
stochastic gradient descent
(1)
Papers
A Video is Worth 10000 Words: Training and Benchmarking with Diverse Captions for Better Long Video Retrieval
WACV 2025
Punching Bag vs. Punching Person: Motion Transferability in Videos
ICCV 2025
BloomVQA: Assessing Hierarchical Multi-modal Comprehension
ACL 2024
DRESS: Instructing Large Vision-Language Models to Align and Interact with Humans via Natural Language Feedback
CVPR 2024
Measuring and Improving Chain-of-Thought Reasoning in Vision-Language Models
NAACL 2024
Trigger Hunting with a Topological Prior for Trojan Detection
ICLR 2022
Comprehension Based Question Answering using Bloom’s Taxonomy
ACL 2021
Dialog without Dialog Data: Learning Visual Dialog Agents from VQA Data
NeurIPS 2020
Grad-CAM: Visual Explanations From Deep Networks via Gradient-Based Localization
ICCV 2017
Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles
NeurIPS 2016