Andrew Lee
16 papers · 2019–2026 · 10 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (10) π Renaissance Researcher (5) π Interdisciplinary Bridge π§ Keyword Pioneer π Academic Marathon (6)
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Taxonomy Completionist
(29)
π
Renaissance Researcher
(5)
π
Interdisciplinary Bridge
π₯
Mega-Team
(22)
β‘
Prolific Year
(6)
ποΈ
Keyword Collector
(74)
β
The Questioner
(2)
π
Century Club
(15)
Conferences
EMNLP (4)
ACL (2)
COLING (2)
EACL (2)
ICLR (1)
ICML (1)
IJCAI (1)
IJCNLP (1)
NAACL (1)
NIPS (1)
Top co-authors
Research topics
Keywords
large language model
(3)
intent classification
(3)
out-of-scope prediction
(2)
text classification
(2)
preference optimization
(1)
graph theory
(1)
benchmark evaluation
(1)
self-supervised learning
(1)
sentiment analysis
(1)
conversational ai
(1)
direct preference optimization
(1)
mental health analysis
(1)
synthetic data evaluation
(1)
task-oriented dialogue
(1)
natural language understanding
(1)
curriculum learning
(1)
low-resource learning
(1)
neural network analysis
(1)
ai safety
(1)
algorithmic fairness
(1)
Papers
From Isolation to Entanglement: When Do Interpretability Methods Identify and Disentangle Known Concepts?
ACL 2026
Eeyore: Realistic Depression Simulation via Expert-in-the-Loop Supervised and Preference Optimization
ACL 2025
ICLR: In-Context Learning of Representations
ICLR 2025
How Does DPO Reduce Toxicity? A Mechanistic Neuron-Level Analysis
EMNLP 2025
Emergence of Hidden Capabilities: Exploring Learning Dynamics in Concept Space
NIPS 2024
Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models
COLING 2024
Towards Algorithmic Fidelity: Mental Health Representation across Demographics in Synthetic vs. Human-generated Data
COLING 2024
A Comparative Multidimensional Analysis of Empathetic Systems
EACL 2024
A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity
ICML 2024
Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search
IJCAI 2024
Empathy Identification Systems are not Accurately Accounting for Context
EACL 2023
Emergent Linear Representations in World Models of Self-Supervised Sequence Models
EMNLP 2023
Micromodels for Efficient, Explainable, and Reusable Systems: A Case Study on Mental Health
EMNLP 2021
An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction
EMNLP 2019
Outlier Detection for Improved Data Quality and Diversity in Dialog Systems
NAACL 2019
An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction
IJCNLP 2019