Andrew Li
16 papers · 2017–2025 · 11 venues · across top CS/AI venues
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Achievements
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π Conference Polyglot Β· Gold π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (50) π Academic Marathon Β· Sprint π£ Hot Topic Early Bird
π
Renaissance Researcher
(8)
π₯
Unstoppable Β· Bronze
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Prolific Year Β· Productive
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Century Club Β· Bronze
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Keyword Collector
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Venues
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Research topics
Machine Learning
(13)
Artificial Intelligence
(8)
Learning Types
(7)
Core AI
(6)
Optimization & Theory
(6)
Application Areas
(5)
Deep Learning
(3)
Mathematics & Optimization
(3)
Natural Language Processing
(3)
Applications
(3)
Core Methods
(3)
Optimization
(3)
Reinforcement Learning
(2)
Architectures
(2)
Bayesian & Probabilistic
(2)
Keywords
causal inference
(4)
neural architecture search
(2)
model scaling
(2)
knowledge distillation
(2)
regret bound
(2)
reinforcement learning
(1)
natural language processing
(1)
contrastive learning
(1)
probabilistic modeling
(1)
online learning
(1)
representation learning
(1)
structure learning
(1)
embedding learning
(1)
sequential decision making
(1)
sample complexity
(1)
off-policy evaluation
(1)
multimodal learning
(1)
vision transformer
(1)
instruction following
(1)
active learning
(1)
Papers
cantnlp@DravidianLangTech-2025: A Bag-of-Sounds Approach to Multimodal Hate Speech Detection
NAACL 2025
EmbedLLM: Learning Compact Representations of Large Language Models
ICLR 2025
ChatHF: Collecting Rich Human Feedback from Real-time Conversations
EMNLP 2024
FLIQS: One-Shot Mixed-Precision Floating-Point and Integer Quantization Search
AutoML 2024
Multimodal Image-Text Matching Improves Retrieval-based Chest X-Ray Report Generation
MIDL 2023
TripLe: Revisiting Pretrained Model Reuse and Progressive Learning for Efficient Vision Transformer Scaling and Searching
ICCV 2023
Dynamic Pricing with Monotonicity Constraint under Unknown Parametric Demand Model
NeurIPS 2022
Learning to Follow Instructions in Text-Based Games
NeurIPS 2022
Markovian Interference in Experiments
NeurIPS 2022
Causal Inference with Selectively Deconfounded Data
AISTATS 2021
Disposable Linear Bandits for Online Recommendations
AAAI 2021
Greedy Approximation Algorithms for Active Sequential Hypothesis Testing
NeurIPS 2021
Learning Treatment Effects in Panels with General Intervention Patterns
NeurIPS 2021
Searching for Fast Model Families on Datacenter Accelerators
CVPR 2021
Bayesian Network Structure Learning with Side Constraints
PGM 2018
Optimal Recovery of Tensor Slices
AISTATS 2017