Katherine Metcalf
11 papers · 2019–2025 · 8 venues · across top CS/AI venues
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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (25)
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Artificial Intelligence
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Learning Types · Machine Learning
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Natural Language Processing
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Reinforcement Learning
(3)
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Deep Learning
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Learning Types · Deep Learning
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Keywords
preference-based reinforcement learning
(3)
policy learning
(2)
representation learning
(2)
hierarchical learning
(1)
parameter-efficient learning
(1)
direct preference optimization
(1)
embedding space
(1)
model uncertainty
(1)
coreference resolution
(1)
language model alignment
(1)
iterative refinement
(1)
out-of-distribution generalization
(1)
cross-lingual alignment
(1)
reinforcement learning from human feedback
(1)
parameter efficient
(1)
self-supervised learning
(1)
sample efficiency
(1)
reward function
(1)
temporal abstraction
(1)
deep reinforcement learning
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Papers
Aligning LLMs by Predicting Preferences from User Writing Samples
ICML 2025
Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs
ICML 2025
On the Way to LLM Personalization: Learning to Remember User Conversations
ACL 2025
Steering into New Embedding Spaces: Analyzing Cross-Lingual Alignment Induced by Model Interventions in Multilingual Language Models
ACL 2025
Can You Rely on Synthetic Labellers in Preference-Based Reinforcement Learning? It’s Complicated
AAAI 2024
Hindsight PRIORs for Reward Learning from Human Preferences
ICLR 2024
On the Limited Generalization Capability of the Implicit Reward Model Induced by Direct Preference Optimization
EMNLP 2024
Whispering Experts: Neural Interventions for Toxicity Mitigation in Language Models
ICML 2024
Sample-Efficient Preference-based Reinforcement Learning with Dynamics Aware Rewards
CoRL 2023
Mirroring to Build Trust in Digital Assistants
Interspeech 2019
Unsupervised Hierarchical Temporal Abstraction by Simultaneously Learning Expectations and Representations
IJCAI 2019