Cheng-Yu Hsieh
16 papers · 2019–2025 · 7 venues · across top CS/AI venues
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large language model
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multimodal language model
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language model
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visual reasoning
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model compression
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domain generalization
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few-shot learning
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image classification
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depth estimation
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rationale extraction
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network pruning
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image editing
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referring expression
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multi-task learning
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deepfake detection
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in-context learning
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text-to-image generation
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feature attribution
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efficient computing
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scene graph generation
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Papers
NVILA: Efficient Frontier Visual Language Models
CVPR 2025
Perception Tokens Enhance Visual Reasoning in Multimodal Language Models
CVPR 2025
RealEdit: Reddit Edits As a Large-scale Empirical Dataset for Image Transformations
CVPR 2025
Synthetic Visual Genome
CVPR 2025
DataComp-LM: In search of the next generation of training sets for language models
NeurIPS 2024
Found in the middle: Calibrating Positional Attention Bias Improves Long Context Utilization
ACL 2024
Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning
EMNLP 2024
Lookback Lens: Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps
EMNLP 2024
Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity
ICML 2024
The Hard Positive Truth about Vision-Language Compositionality
ECCV 2024
The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better
NeurIPS 2024
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes
ACL 2023
SugarCrepe: Fixing Hackable Benchmarks for Vision-Language Compositionality
NeurIPS 2023
Understanding Programmatic Weak Supervision via Source-aware Influence Function
NeurIPS 2022
Evaluations and Methods for Explanation through Robustness Analysis
ICLR 2021
On the (In)fidelity and Sensitivity of Explanations
NeurIPS 2019