Shengbang Tong
16 papers · 2022–2026 · 8 conferences · across top CS/AI conferences
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(2)
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(2)
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NIPS (6)
ICCV (3)
ICLR (2)
AAAI (1)
ACL (1)
CVPR (1)
ICML (1)
JMLR (1)
Top co-authors
Research topics
Keywords
multimodal learning
(5)
representation learning
(4)
self-supervised learning
(4)
large language model
(3)
vision-language model
(3)
vision language model
(3)
multimodal large language model
(3)
visual representation learning
(3)
contrastive learning
(3)
token compression
(2)
sparse rate reduction
(2)
benchmark evaluation
(2)
transformer architecture
(2)
visual representation
(2)
visual reasoning
(2)
visual grounding
(2)
decision making
(1)
manifold learning
(1)
adversarial robustness
(1)
vision transformer
(1)
Papers
Seeing from Another Perspective: Evaluating Multi-View Understanding in MLLMs
AAAI 2026
MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark
ACL 2025
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
ICML 2025
MetaMorph: Multimodal Understanding and Generation via Instruction Tuning
ICCV 2025
Scaling Language-Free Visual Representation Learning
ICCV 2025
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs
CVPR 2024
Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning
NIPS 2024
Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models
ICLR 2024
White-Box Transformers via Sparse Rate Reduction: Compression Is All There Is?
JMLR 2024
Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs
NIPS 2024
Connecting Joint-Embedding Predictive Architecture with Contrastive Self-supervised Learning
NIPS 2024
Unsupervised Manifold Linearizing and Clustering
ICCV 2023
White-Box Transformers via Sparse Rate Reduction
NIPS 2023
Mass-Producing Failures of Multimodal Systems with Language Models
NIPS 2023
Incremental Learning of Structured Memory via Closed-Loop Transcription
ICLR 2023
Revisiting Sparse Convolutional Model for Visual Recognition
NIPS 2022